Dissertations / Theses on the topic 'Medical Medical Imaging'

Breast cancer is the most crucial cancer type among all other cancer types. There are many imaging techniques used to screen breast carcinoma. These are mammography, ultrasound, computed tomography, magnetic resonance imaging, infrared imaging, positron emission tomography and electrical impedance tomography. However, there is no gold standard in breast carcinoma diagnosis. The object of this study is to create a hybrid system that uses thermal and electrical imaging methods together for breast cancer diagnosis. Body tissues have different electrical conductivity values depending on their state of health and types. Consequently, one can get information about the anatomy of the human body and tissue&rsquo
s health by imaging tissue conductivity distribution. Due to metabolic heat generation values and thermal characteristics that differ from tissue to tissue, thermal imaging has started to play an important role in medical diagnosis. To increase the temperature contrast in thermal images, the characteristics of the two imaging modalities can be combined. This is achieved by implementing thermal imaging applying electrical currents from the body surface within safety limits (i.e., thermal imaging in active mode). Electrical conductivity of tissues changes with frequency, so it is possible to obtain more than one thermal image for the same body. Combining these images, more detailed information about the tumor tissue can be acquired. This may increase the accuracy in diagnosis while tumor can be detected at deeper locations. Feasibility of the proposed technique is investigated with analytical and numerical simulations and experimental studies. 2-D and 3-D numerical models of the female breast are developed and feasibility work is implemented in the frequency range of 10 kHz and 800 MHz. Temporal and spatial temperature distributions are obtained at desired depths. Thermal body-phantoms are developed to simulate the healthy breast and tumor tissues in experimental studies. Thermograms of these phantoms are obtained using two different infrared cameras (microbolometer uncooled and cooled Quantum Well Infrared Photodetectors). Single and dual tumor tissues are determined using the ratio of uniform (healthy) and inhomogeneous (tumor) images. Single tumor (1 cm away from boundary) causes 55 °
mC temperature increase and dual tumor (2 cm away from boundary) leads to 50 °
mC temperature contrast. With multi-frequency current application (in the range of 10 kHz-800 MHz), the temperature contrast generated by 3.4 mm3 tumor at 9 mm depth can be detected with the state-of-the-art thermal imagers.

It is estimated that over half of current adults within Great Britain under the age of 65 will be diagnosed with cancer at some point in their lifetime. Medical Imaging forms an essential part of cancer clinical protocols and is able to furnish morphological, metabolic and functional information. The imaging of molecular interactions of biological processes in vivo with Positron Emission Tomography (PET) is informative not only for disease detection but also therapeutic response. The qualitative and quantitative accuracy of imaging is thus vital in the extraction of meaningful and reproducible information from the images, allowing increased sensitivity and specificity in the diagnosis and precision of image guided treatment. Furthermore the utilization of complementary information obtained via Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) in integrated PET-CT and PET-MR devices offers the potential for the synergistic effects of hybrid imaging to provide increased detection and precision of diagnosis with reduced radiation dose in a fully comprehensive single imaging examination. With the increasing sophistication in imaging technology respiratory organ motion during imaging has demonstrated itself to be a major degrading factor of PET image resolution. A modest estimate of respiratory motion amplitude of 5mm, results in PET system resolution degrading from ≈ 5mm to ≈8.5mm. This evidently has an impact on cancer lesion detectability. Therefore accurate and robust methods for respiratory motion correction are required for both clinical effectiveness and economic justification for purchasing state of the art hybrid PET scanners with high resolution capabilities. In addition the judicious use of imaging resources from hybrid imaging devices coupled with advanced image processing / acquisition protocols will allow optimization of data used for improving quantitative accuracy of PET images and those used for clinical interpretation. In essence it would prove impractical to use the MR scanner purely for monitoring respiratory motion. Numerous methods exist to attempt to correct PET imaging for respiratory motion. As presented in this thesis many methods demonstrate themselves to be ineffective in the clinical setting where the patients breathing patterns appear irregular in comparison to the idealized situation of regular periodic motion. Advanced respiratory motion correction techniques utilize hybrid PET/CT, PET/MR scanners coupled with an external source of information which serves as a surrogate to build a static correspondence to the estimated internal respiratory motion. Static models however are unable to adapt to their external environment and do not consider time dependent changes in the state of a system. A further confounding factor in the development and assessment of motion correction schemes for medical imaging data is the inability to acquire volumetric data with high contrast and high spatial and temporal resolution which serves as a ground truth for quantifying model accuracy and confidence. This thesis addresses both problems by analysing respiratory motion correspondence modelling under a manifold learning and alignment paradigm which may be used to consolidate many of the respiratory motion estimation models that exist today. A Bayesian approach is adopted in this work to incorporate a-priori information into the model building stage for a more robust, flexible adaptive respiratory motion estimation / correction framework. This thesis constructs and tests the first proposed adaptive motion model to correlate a surrogate signal with internal motion. This adaptive approach allows the relationship between external surrogate signal and internal motion to change dependent upon breathing pattern and system noise. The adaptive model was compared to a state-of the-art static model and allows more accurate motion estimates to be made when the patient is breathing with an irregular pattern. Testing performed on MRI data from 9 volunteers demonstrated the adaptive model was statistically more significant (p < 0.001) in the presence of irregular motion in comparison to a static model. The adaptive Kalman model on average reduced the error in motion by 30% in comparison to the static model. Utilizing the adaptive model during a typical PET study would theoretically result in ≈ 10% increase in PET resolution in comparison to relying on a static model alone for motion correction. The adaptive Kalman model has the capability to increase the performance of PET system resolution from ≈ 8.5mm to ≈ 5.8mm, ≈ 30%. A simulated PET study also demonstrated ≈ 30% increase in tumour uptake when using motion correction. Also demonstrated in the thesis is the first method to acquire volumetric imaging data from sparse MR samples during free breathing to allow the realization of high contrast, high resolution 4D models of respiratory motion using limited acquired data. The developed framework facilitates greater freedom in the acquisition of free breathing respiratory motion sequences which may be used to inform motion modelling methods in a range of imaging modalities as well as informing the development of generalizable models of human respiration. It is shown that the developed approach can provide equivalent motion vector fields in comparison to fully sampled 4D dynamic data. The incorporation of the manifold alignment step into the sparse motion model reduces the error in motion estimates by ≈ 16%. Example images of propagated motion are also presented as supplementary information. The thesis concludes by generalizing the concepts in this work and looking to utilize the developed methods to other problems in the medical imaging arena.

Mestrado em Engenharia de Computadores e Telemática
A aplicação CapView utiliza um algoritmo de classificação baseado em SVM (Support Vector Machines) para automatizar a segmentação topográfica de vídeos do trato intestinal obtidos por cápsula endoscópica. Este trabalho explora a aplicação de processadores gráficos (GPU) para execução paralela desse algoritmo. Após uma etapa de otimização da versão sequencial, comparou-se o desempenho obtido por duas abordagens: (1) desenvolvimento apenas do código do lado do host, com suporte em bibliotecas especializadas para a GPU, e (2) desenvolvimento de todo o código, incluindo o que é executado no GPU. Ambas permitiram ganhos (speedups) significativos, entre 1,4 e 7 em testes efetuados com GPUs individuais de vários modelos. Usando um cluster de 4 GPU do modelo de maior capacidade, conseguiu-se, em todos os casos testados, ganhos entre 26,2 e 27,2 em relação à versão sequencial otimizada. Os métodos desenvolvidos foram integrados na aplicação CapView, utilizada em rotina em ambientes hospitalares.
The CapView application uses a classification algorithm based on SVMs (Support Vector Machines) for automatic topographic segmentation of gastrointestinal tract videos obtained through capsule endoscopy. This work explores the use graphic processors (GPUs) to parallelize the segmentation algorithm. After an optimization phase of the sequential version, two new approaches were analyzed: (1) development of the host code only, with support of specialized libraries for the GPU, and (2) development of the host and the device’s code. The two approaches caused substantial gains, with speedups between 1.4 and 7 times in tests made with several different individual GPUs. In a cluster of 4 GPUs of the most capable model, speedups between 26.2 and 27.2 times were achieved, compared to the optimized sequential version. The methods developed were integrated in the CapView application, used in routine in medical environments.

The goal of this research is to develop computational methods for predicting how a given medical imaging system and reconstruction algorithm will perform when mathematical observers for tumor detection use the resulting images. Here the mathematical observer is the ideal observer, which sets an upper limit to the performance as measured by the Bayesian risk or receiver operating characteristic analysis. This dissertation concentrates on constructing the ideal observer in complex detection problems and estimating its performance. Thus the methods reported in this dissertation can be used to approximate the ideal observer in real medical images. We define our detection problem as a two-hypothesis detection task where a known signal is superimposed on a random background with complicated distributions and embedded in independent Poisson noise. The first challenge of this detection problem is that the distribution of the random background is usually unknown and difficult to estimate. The second challenge is that the calculation of the ideal observer is computationally intensive for non stylized problems. In order to solve these two problems, our work relies on multiresolution analysis of images. The multiresolution analysis is achieved by decomposing an image into a set of spatial frequency bandpass images so each bandpass image represents information about a particular fitness of detail or scale. Connected with this method, we will use three types of image representation by invertible linear transforms. They are the orthogonal wavelet transform, pyramid transform and independent component analysis. Based on the findings from human and mammalian vision, we can model textures by using marginal densities of a set of spatial frequency bandpass images. In order to estimate the distribution of an ensemble of images given the empirical marginal distributions of filter responses, we can use the maximum entropy principle and get a unique solution. We find that the ideal observer calculates a posterior mean of the ratio of conditional density functions, or the posterior mean of the ratio of two prior density functions, both of which are high dimensional integrals and have no analytic solution usually. But there are two ways to approximate the ideal observer. The first one is a classic decision process; that is, we construct a classifier following feature extraction steps. We use the integrand of the posterior mean as features, which are calculated at the estimated background close to the posterior mode. The classifier combines these features to approximate the integral (or the ideal observer). Finally, if we know both the conditional density function and the prior density function then we can also approximate the high dimensional integral by Monte Carlo integration methods. Since the calculation of the posterior mean is usually a very high dimensional integration problem, we must construct a Markov chain, which can explore the posterior distribution efficiently. We will give two proposal functions. The first proposal function is the likelihood function of random backgrounds. The second method makes use of the multiresolution representation of the image by decomposing the image into a set of spatial frequency bands. Sampling one pixel in each band equivalently updates a cluster of pixels in the neighborhood of the pixel location in the original image.

This thesis addresses two problems in medical imaging, the development of a system for 3D imaging with ultrasound and a system for making titanium prostheses for cranioplasty. Central to both problems is the construction and depiction of surfaces from volume data where the data is not acquired on a regular grid or is incomplete. A system for acquiring 3D pulse-echo ultrasound data using a conventional 2D ultrasound scanner equipped with an electro-magnetic spatial locator is described. The non-parallel nature of 2D B-scan slices acquired by the system requires the development of new visualisation algorithms to depict three dimensional structures. Two methods for visualising iso-valued surfaces from the ultrasound data are presented. One forms an intermediate volume reconstruction suitable for conventional ray-casting while the second method renders surfaces directly from the slice data. In vivo imaging of human anatomy is used to demonstrate reconstructions of tissue surfaces. Filtering and spatial compounding of scan data is used to reduce speckle. The manifestation of 2D artefacts in 3D surface reconstructions is also illustrated. Pulse-echo ultrasound primarily depicts tissue boundaries. These are characterised by incomplete acoustic interfaces contaminated by noise. The problem of reconstructing tissue interfaces from ultrasound data is viewed as an example of the general problem of reconstructing an object's shape from unorganised surface data. A novel method for reconstructing surfaces in the absence of a priori knowledge of the object's shape, is described and applied to 3D ultrasound data. The method uses projections through the surface data taken from many viewpoints to reconstruct surfaces. Aspects of the method are similar to work in computer vision concerning the determination of the shape of 3D objects from their silhouettes. This work is extended significantly in this thesis by considering the reconstruction of incomplete objects in the presence of noise and through the development of practical algorithms for pixel and voxel data. Furthermore, the reconstruction of realistic, non-convex objects is considered rather than simple geometric objects. 2D and 3D ultrasound data derived from phantoms, as well as artificial data, are used to demonstrate reconstructions. The second problem studied in this thesis concerns designing cranial implants to repair defects in the skull. Skull surfaces are extracted from X-ray CT data by ray-casting iso-valued surfaces. A tensor product B-spline interpolant is used in the ray-caster to reduce ripples in the surface data due to partial voluming and the large spacing between CT slices. The associated surface depth-maps are characterised by large irregular holes which correspond to the defect regions requiring repair. Defects are graphically identified by a user in surface-rendered images. Radial basis function approximation is introduced as a method of interpolating the surface of the skull across these defect regions. The fitted surface is used to produce CNC milling instructions to machine a mould in the shape of the surface from a block of hard plastic resin. A cranial implant is then formed by pressing flat titanium plate into the mould under high pressure in a hydraulic press. The system improves upon current treatment procedures by avoiding the manual aspects of fashioning an implant. It is also suitable when other techniques which use symmetry to reconstruct the skull are inadequate or not possible. The system has been successfully used to treat patients at Christchurch Hospital. Radial basis function (RBF) approximation has previously been restricted to problems where the number of interpolation centres is small. The use of newly developed fast methods for evaluating radial basis interpolants in the surface interpolation software results in a computationally efficient system for designing cranial implants and demonstrates that RBFs are potentially of wide interest in medical imaging and engineering problems where data does not lie on a regular grid.

Mestrado em Engenharia de Computadores e Telemática
Hoje em dia, as instituições de cuidados de saúde, utilizam a telemedicina para suportar ambientes colaborativos. Na área da imagem médica digital, a quantidade de dados tem crescido substancialmente nos últimos anos, requerendo mais infraestruturas para fornecer um serviço com a qualidade desejada. Os computadores e dispositivos com acesso à Internet estão acessíveis em qualquer altura e em qualquer lugar, criando oportunidades para partilhar e utilizar recursos online. Uma enorme quantidade de processamento computacional e armazenamento são utilizados como uma comodidade no quotidiano. Esta dissertação apresenta uma plataforma para suportar serviços de telemedicina sobre a cloud, permitindo que aplicações armazenem e comuniquem facilmente, utilizando qualquer fornecedor de cloud. Deste modo, os programadores não necessitam de se preocupar onde os recursos vão ser instalados a as suas aplicações não ficam limitadas a um único fornecedor. Foram desenvolvidas duas aplicações para tele-imagiologia com esta plataforma: repositório de imagens médicas e uma infraestrutura de comunicações entre centros hospitalares. Finalmente, a arquitetura desenvolvida é genérica e flexível permitindo facilmente a sua expansão para outras áreas aplicacionais e outros serviços de cloud.
Healthcare institutions resort largely, nowadays, to telemedicine in order to support collaborative environments. In the medical imaging area, the huge amount of medical volume data has increased over the past few years, requiring high-performance infrastructures to provide services with required quality. Computing devices and Internet access are now available anywhere and at anytime, creating new opportunities to share and use online resources. A tremendous amount of ubiquitous computational power and an unprecedented number of Internet resources and services are used every day as a normal commodity. This thesis presents a telemedicine service platform over the Cloud that allows applications to store information and to communicate easier, using any Internet cloud provider. With this platform, developers do not concern where the resources will be deployed and the applications will not be restricted to a specific cloud vendor. Two tele-imagiologic applications were developed along with this platform: a medical imaging repository and an interinstitutional communications infrastructure. Lastly, the architecture developed is generic and flexible to expand to other application areas and cloud services.

This thesis investigated novel deep learning techniques for advanced medical imaging applications. It addressed three major research issues of employing deep learning for medical imaging applications including network architecture, lack of training data, and generalisation. It proposed three new frameworks for CNN network architecture and three novel transfer learning methods. The proposed solutions have been tested on four different medical imaging applications demonstrating their effectiveness and generalisation. These solutions have already been employed by the scientific community showing excellent performance in medical imaging applications and other domains.

L’obiettivo di questo lavoro è quello di contribuire allo sviluppo di un’epistemolo-gia dell’imaging medico, intendendo con questo termine sia le immagini utilizzate a fini diagnostici, sia le tecnologie che le producono. La mia tesi principale è che le tecnologie di imaging medico non si limitano a produrre immagini più o meno accurate degli organi interni e di alcuni processi fisiologici, ma piuttosto trasformano il corpo in un oggetto scientifico, operando un cambiamento profondo della sua visibilità. Gli strumenti di imaging mutano il corpo in un oggetto visivo che può essere osservato in condizioni sperimentali. A differenza del corpo reale, tale oggetto può essere archiviato, consultato, condiviso, misurato e manipolato in varie maniere. Questa tesi di fondo è accompagnata da altre due: (1) Le immagini diagnostiche, come tutte le immagini scientifiche, sono veri e propri strumenti cognitivi, strumenti epistemici integrati in un quadro teorico-pratico specifico; (2) Un’immagine che rivela l’interno dell’organismo ha significato e valore diagnostico solo nell’ambito di una specifica concettualizzazione del corpo e della malattia, di conseguenza uno studio sull’epistemologia dell’imaging medico non si potrà limitare a esaminare le immagini diagnostiche in quanto immagini, ma dovrà analizzarle anche nella loro veste di strumenti di diagnosi medica. Per questo motivo nel primo capitolo della dissertazione traccio le linee generali delle condizioni di possibilità storiche e concettuali della radiografia -- la prima tecnologia di imaging medico -- inventata nel 1895. Lo scopo è quello di comprendere quali teorie e pratiche mediche dovessero essere vigenti alla fine del XIX secolo, affinché immagini che parevano ombre del corpo interno potessero essere considerate strumenti diagnostici. La spiegazione da me proposta è che la rilevanza diagnostica della radiografia si fonda sulla concettualizzazione di corpo, malattia e diagnosi resa operativa dall’anatomia clinica già alla fine del XVIII secolo. Seguendo e supportando questa linea di ragionamento mostro che lo stetoscopio, inventato nel 1816, può essere considerato il predecessore materiale e intellettuale dell’imaging medico perché introdusse una primitiva forma di mediazione sensoriale nel campo della diagnostica e permise al medico di esplorare dall’esterno le profondità del corpo del paziente, estraendone segni di malattia. Lo stetoscopio è solo il primo di una vasta famiglia di strumenti inventati nel XIX secolo per visualizzare diversi aspetti della morfologia interna e della fisiologia del vivente. Sebbene ciascuno di questi strumenti rispondesse a specifiche necessità diagnostiche e ponesse specifici problemi epistemologici, si possono identificare alcune caratteristiche comuni: tutti avevano come obbiettivo quello di sostituire le sensazioni soggettive dei pazienti e dei medici con indici oggettivi di salute e malattia; tutti creavano registri visivi dell’interno del corpo umano che potevano essere archiviati, recuperati e condivisi da diversi medici; tutti richiedevano la creazione di un linguaggio specializzato, condiviso da una comunità medico-scientifica; tutti creavano una progressiva separazione tra il corpo del paziente e il corpo del medico. È in questo complesso scenario di pratiche, oggetti, raffigurazioni e idee che la radiografia fece la sua comparsa e acquisì la sua funzione diagnostica. Nel secondo capitolo prendo in esame la nascita della fotografia, al fine di comprendere in che modo la prima tecnologia di produzione meccanica di immagini influenzò la medicina. I principali riferimenti teorici di questo capitolo sono dati dalla semiotica di Charles Sanders Peirce, in particolare la sua classificazione dei segni in indici, icone e simboli, e dalla riflessione di Walter Benjamin sulla serie fotografica (produzione e riproduzione meccanica di un’immagine e del corpo in essa rappresentato), sull’intrinseco potenziale analitico e di dissezione della fotografia (il fotografo come chirurgo), e sull’inconscio ottico (fotografia come protesi che arricchisce e trasforma l’esperienza sensibile). Basandomi su questi autori e esaminando i lavori dei primi medici-fotografi nell’ambito della psichiatria, dermatologia, fisiologia e neurologia, mostro che le serie fotografiche raccolte in riviste mediche, manuali di studio e archivi ospedalieri produssero uno sguardo clinico in senso foucauldiano. Sostengo, inoltre, che la serie fotografica faceva parte di un più ampio apparato sperimentale che includeva il paziente, la macchina fotografica e l’osservatore il cui scopo era trasformare il corpo e la malattia in oggetti visivi che potessero essere sottoposti ad analisi scientifica. Nel terzo capitolo discuto il problema del referente invisibile, ossia analizzo i processi attraverso cui le immagini fotografiche di oggetti invisibili vengono dotate di significato. Probabilmente questo è il problema fondamentale di qualunque tipo di imaging scientifico. Quando il referente di una fotografia è invisibile, la modalità iconica di significazione non può essere messa in atto, perché nell’immagine prodotta dallo strumento (sia esso meccanico o elettronico) non possiamo riconoscere nessuna similitudine con l’oggetto rappresentato. Di fatto, potremmo dire che in questi casi l’immagine non assomiglia a nulla. Come sappiamo, dunque, se l’oggetto che vediamo nella fotografia – per esempio una cellula o una lesione tubercolare – è davvero là, e possiede davvero l’aspetto mostrato dall’immagine? Sulla scorta dell’analisi teorica sviluppata nel capitolo precedente, difendo l’idea che la visualizzazione dell’invisibile richieda una peculiare combinazione delle modalità di significazione indicale, iconica e simbolica. La mia argomentazione è costruita in opposizione al concetto di oggettività meccanica proposto da Lorraine Daston e Peter Galison. In particolare, dimostro che l’idea di oggettività meccanica come soppressione moralizzante del soggetto proposta dai due storici è una caricatura delle idee e pratiche sviluppate dagli scienziati del XIX secolo per risolvere il problema della visualizzazione dell’invisibile. La mia argomentazione si articola in tre momenti, corrispondenti all’analisi del problema dell’oggettività e della significazione delle immagini in tre diversi ambiti: microfotografia, cronofotografia e radiografia. Nel quarto capitolo affronto il problema del valore cognitivo delle immagini, sostenendo che le immagini sono strumenti epistemici (nel senso forte, non metaforico della parola strumento) e che rappresentazione e osservazione non sono mai atti puramente automatici, perché richiedono sempre una componente creativa. Come nel capitolo precedente, parte del mio discorso è una refutazione della posizione di Daston e Galison, in particolare per quanto riguarda le loro affermazioni sulla natura passiva di certe rappresentazioni visive. Secondo Daston e Galison, infatti, fino allo sviluppo delle tecnologie digitali, le immagini scientifiche erano mere ri-presentazioni [re-presentations] del mondo, miranti a copiare la natura. Con la comparsa del digitale, invece, si è passati a un’epoca in cui le immagini sono presentazioni [presentations], perché attraverso di esse l’osservatore può visualizzare l’oggetto in mutevoli forme, manipolandolo virtualmente. La mia critica a questa posizione è basata su argomenti storici e teorici. Sul piano storico mostro che i primi tentativi di creare immagini mediche manipolabili risalgono almeno al XVI secolo. Sul piano teorico, ricorrendo alla letteratura prodotta in campi così diversi come la teoria dell’arte e le neuroscienze, dimostro che la nozione di ricezione passiva di un’immagine è insostenibile, perché le immagini coinvolgono sempre l’osservatore in un atto corporeo di percezione che sollecita non solo sensazioni visive, ma anche sensazioni tattili e reazioni motorie. Inoltre, sostengo che l’enfasi posta da Daston e Galison sul nanoimaging come l’unica tecnologia che permette di manipolare l’oggetto durante la fase di produzione di un’immagine è fuorviante. Infatti, anche nei casi in cui non raggiungono le vette di sofisticazione tecnologica proprie delle nano-immagini, le immagini scientifiche sono sempre il risultato di una manipolazione dell’oggetto naturale rappresentato. Un’immagine scientifica non può essere una mera copia della natura, perché è sempre parte di una praxis sperimentale il cui obiettivo è comprendere un fenomeno naturale, non solo riprodurlo. Per corroborare questa idea analizzo alcune pratiche concrete di significazione di immagini scientifiche, prendendo in esame documenti scritti (analisi semiotica di un articolo di radiologia) e pratiche materiali (etnografia di laboratorio riguardante l’interpretazione di immagini di elettroforesi in biologia molecolare e descrizione di un caso di significazione di immagini di microscopia elettronica). Questa analisi permette di fare tre osservazioni: (1) Il processo di significazione delle immagini scientifiche è un processo distribuito; (2) Le immagini scientifiche possono essere considerate strumenti di ricerca, nel senso che scienziati e medici le manipolano in varie forme al fine di esplorare aspetti diversi del loro oggetto di studio; (3) Le immagini scientifiche vanno comprese come fenomeni artificiali controllati prodotti allo scopo di ridefinire la visibilità degli oggetti naturali. Per approfondire meglio quest’ultima idea, nel capitolo finale introduco il concetto di fenomenotecnica sviluppato da Gaston Bachelard. La nozione di fenomenotecnica non può essere applicata direttamente all’imaging medico, ma alcuni degli elementi che caratterizzano il concetto bachelardiano offrono spunti importanti per pensare l’imaging medico. Il primo di questi elementi è l’idea che per studiare un fenomeno naturale, lo scienziato deve innanzitutto trasformarlo in un oggetto scientifico. Il secondo elemento, strettamente legato al primo, è che l’esperienza scientifica è necessariamente mediata, e tale mediazione ha un carattere intellettuale e materiale. Questo significa che la costruzione di strumenti e lo sviluppo di tecnologie non sono un prodotto della scienza, ma piuttosto un elemento interno al processo scientifico. La tecnologia è integrata nella scienza, perché la nostra apprensione? scientifica del mondo è necessariamente mediata da strumenti. Gli strumenti, a loro volta, sono materializzazioni di un vasto corpo di conoscenze e pratiche scientifiche (nel caso dell’imaging digitale tale sapere ha un carattere eminentemente matematico). Scienza e tecnologia, dunque, si costituiscono reciprocamente. A partire da queste considerazioni propongo un descrizione dell’imaging medico in termini di fenomenotecnica, utilizzando tale concetto come parola chiave attorno alla quale riorganizzare le idee discusse in precedenza. In primo luogo ricorro al concetto di fenomenotecnica per spiegare come le immagini diagnostiche mediano l’esperienza sensoriale e intellettuale del medico. Successivamente descrivo le immagini diagnostiche in termini di fenomeni artificiali (riconfigurazione visiva di segnali non visivi) che funzionano come simulazioni del corpo del paziente e che materializzano ambiti della conoscenza differenti (dalla medicina alla fisica, passando per l’ingegneria). Infine, mostro che la significazione corretta ed efficace di un’immagine diagnostica richiede una fenomenotecnica dell’osservatore. Per riconoscere i segni di malattia in un’immagine dell’interno del corpo è necessario padroneggiare le regole implicite ed esplicite che permettono di dare senso al nuovo dominio sensoriale prodotto dalla tecnologia. Ciò implica un abbandono dei modi spontanei di percezione-significazione e il passaggio attraverso un processo educativo che modula le capacità percettive. L’osservatore specializzato è un osservatore che ha preso parte a un processo di formazione che trasforma profondamente la visione naturale, inserendo l’atto del guardare all’interno di una vasta rete epistemica che include conoscenze teoriche e pratiche concrete.
The objective of this dissertation is to contribute to the development of an epistemology of medical imaging. My central thesis is that medical imaging does not merely produce more or less accurate pictures of the inner organs, it rather transforms the living body into a scientific object by changing its very visibility. The imaging apparatus turns the body into a visual object that can be observed under experimental conditions: unlike the real body, it can be filed, retrieved, shared, measured and manipulated in several ways. This main thesis is accompanied by two others: first, diagnostic images, as all scientific images, are actual cognitive instruments, epistemic objects inscribed within theoretical contexts and experimental practices. Second, an image of the inner body has diagnostic meaning and value only in the scope of a specific conceptualization of the body and its ailments. Accordingly, if we are to develop an epistemology of medical imaging, we cannot limit our analysis to diagnostic images qua images, we also have to understand them qua diagnostic instruments. This is why at in the first chapter of the dissertation I take into examination the historical and conceptual conditions of possibility of radiography -- the first medical imaging technology, invented in 1895. My aim is to understand what medical theories and practices had to be at work in the nineteenth century, for those shadow-images produced by the X-ray apparatus to be perceived and employed as diagnostic devices. I argue that the diagnostic relevance of radiography is rooted in the conceptualization of body, disease and diagnosis put forward by clinical anatomy already at the end of the eighteenth century. I also defend the idea that the stethoscope, developed in 1816, was the material and intellectual predecessor of medical imaging, because it introduced a primitive form of mediated perception in medical diagnosis, and allowed the clinician to explore from the outside the inner body of the living patient, extracting signs of illness. The stethoscope was only the first of a vast array of instruments invented in the nineteenth century to visualize different aspects of the inner morphology and physiology of the living body. Each of these instruments fulfilled specific diagnostic aims and posed distinct epistemological problems, but all of them shared some commonalities: they were meant to replace the subjective sensations of patients and doctors with objective indices of health and disease; they created visual records of the inner body that could be filed, retrieved and shared among physicians; they required the development of a specialized language agreed upon by a community of experts; they created a progressive physical separation between the body of the patient and the body of the physician. It was in this complex scenario of medical practices, objects, images and ideas that radiography appeared and progressively acquired its diagnostic function. In the second chapter I take into account the early developments of medical photography in order to understand how the first technology for the production of mechanical images entered and influenced the domain of medicine. The main theoretical references in this chapter are Charles Sanders Peirce's semiotics, in particular, his classification of signs in indices, icons and symbols, and Walter Benjamin's reflections on the photographic series (mechanical production and reproduction of an image and of the body it represents), on the intrinsic analytic and dissecting potential of photography (the photographer as a surgeon), and on the optical unconscious (photography as a prosthesis that enriches and transforms our sensorial experience). Drawing on these authors, and analyzing the works of early physicians-photographers in psychiatry, dermatology, neurology and physiology, I show that the photographic series collected in medical journals, manuals and hospital archives, produced a clinical gaze in the Foucauldian sense. I also argue that the photographic series was part of a larger experimental apparatus, which encompassed the patient, the camera and the observer, and whose aim was to turn the body and disease into a visual object available for scientific analysis. In the third chapter I discuss the problem of the invisible referent, that is, I analyze the processes whereby photographs that reveal invisible phenomena are endowed with meaning. This is likely to be the fundamental problem of all scientific imaging. When the referent of a picture is invisible, the iconic mode of signification fails, because in this case the image produced by the mechanical or electronic apparatus does not look like anything we already know, it resembles nothing. So, how do we know that the object we see in the photograph -- e.g., a cell or a tubercular lesion -- is really there and does really look like that? Drawing on the theoretical analysis developed in the previous chapter, I maintain that the visualization of the invisible entails a peculiar combination of the indexical, iconic and symbolic modes of signification. My reasoning opposes Lorraine Daston and Peter Galison's idea of mechanical objectivity, and demonstrates that their notion of mechanical objectivity as the moralizing suppression of subjectivity is a caricature of the actual ideas and practices developed by the scientists of the nineteenth century to deal with the problem of visualizing the invisible. The argument is articulated in three moments, corresponding to the analysis of the problem of objectivity and image signification in microphotography, chronophotography, and radiography. In the fourth chapter I argue that images are cognitive tools and that representation and observation are never an act of automated repetition, they always entail a creative component. As in the previous chapter, part of my discourse is built in contrast with Daston and Galison, challenging their claims concerning the passive nature of representation. For these authors, until the development of digital technologies for image manipulation, scientific images were mere re-presentations of the world, focused on copying nature. Computer images, on the contrary, are presentations, because the observer can virtually manipulate them so that they show the object in ever changing ways. I criticize this classification of scientific images with historical and theoretical arguments. From the historical point of view, I show that at least since the sixteenth century there have been attempts to create images that can be actually manipulated by the observer. From the theoretical perspective, I draw on a variety of literature spanning from art theory to neuroscience, to demonstrate that the very notion of a passive representation is unsustainable, because images always engage the observer in an embodied act of perception, which elicits not only visual, but also tactile sensations and motor reactions. Moreover, I argue that Daston and Galison's emphasis on nanoimaging as the only technology that allows manipulating the object of study during the process of image production is misleading. In fact, even when they do not reach the peaks of technological sophistication that characterizes nanoimages, scientific images are the result of some manipulation of the natural object they represent. A scientific image cannot be a passive copy of nature, because it is part of an experimental praxis, whose goal is to understand natural phenomena, not just to reproduce them. To corroborate this idea I explore actual scientific practices of image signification, taking into account written documents (semiotic analysis of a radiology article) and material practices (laboratory ethnography describing the interpretation of electrophoresis images in a molecular biology laboratory, and description of an example of signification of electron microscopy pictures). From this analysis three remarks can be put forward: (1) the process of signification of scientific images has a distributed character, because it can involve different persons, objects and activities; (2) scientific images can be considered experimental tools, in the sense that scientists and physicians handle them in several forms in order to explore different aspects of their object of study; (3) scientific images are to be understood as controlled, artificial phenomena produced with the aim of redefining the visibility of natural objects. In order to clarify this latter idea, in the final chapter I introduce Gaston Bachelard's concept of phenomenotechnique. Although the idea of phenomenotechnique cannot be directly applied to medical imaging, there are two characterizing elements of this concept that provide important insights for conceptualizing medical imaging. The first is the idea that in order to study a natural phenomenon, scientists must previously transform it into a scientific object. The second, closely related to the former, is that scientific experience is by necessity mediated, and such mediation has both an intellectual and material character. This means that the development of instruments and new technologies is not a second-order product of science, it is part and parcel of the scientific process. Technology is embedded into science, because our scientific grasping of the world is necessarily mediated by instruments; scientific instruments, in turn, are materializations of a vast body of scientific knowledge and practices (in the case of digital imaging this knowledge has an eminently mathematical character). Thus, science and technology are reciprocally constituted. On these grounds I propose a description of medical imaging in terms of phenomenotechnique, using this concept as a key-word around which to reorganize the ideas previously discussed. Firstly, I resort to the concept of phenomenotechnique to gain insights into how diagnostic images mediate the physician's sensory and intellectual experience. Second, I give an account of diagnostic images as artificial phenomena (visual reconfigurations of non-visual signals) that work as simulations of the patient's body, and that reify different domains of knowledge (from medicine to physics and engineering). Finally, I argue that the proper and efficient signification of a diagnostic image requires a phenomenotechnique of the observer. To recognize the signs of disease in an image of the inner body, one has to master the explicit and implicit rules necessary to make sense of the novel sensory domain produced by the technological apparatus. This implies abandoning spontaneous modes of perception and signification to engage in a process of educated perception. The expert viewer goes through a formal and informal training that deeply transforms natural vision, by placing the act of watching within a wide epistemic network that encompasses both theoretical and practical knowledge.

In ultrasound array imaging, the beamforming operation is performed by aligning and processing the received echo signals from each individual array element to form a complete image. This operation can be performed in many different ways, where adaptive and non-adaptive beamformers are considered as the main categories. Adaptive beamformers exploit the statistical correlation between the received data to find a weighting value at the focal point, instead of using a fixed weighting window in non-adaptive beamforming. This results in a significant improvement in the image quality in terms of resolution and sidelobes reduction. This improvement is necessary for ultrafast imaging because of the lack of focusing in Plane Wave Imaging (PWI) that results in lowering the SNR, and thus the produced imaging quality is reduced. This thesis analyses different adaptive beamforming techniques for ultrafast imaging. For accurate medical diagnosis, the frame rate, the imaging resolution, contrast and speckle homogeneity are all considered as important parameters that contribute to the final imaging result. To be able to evaluate each technique by minimizing the effect of external parameters, two different analysis were performed. First an empirical expression for PWI lateral resolution is produced after studying the effect of the imaging parameters on this imaging method. Then a method for selecting the suitable steering angles in Compound Plane- Wave Imaging (CPWI) is introduced, with a detailed explanation for the effect of the compound angles on resolution and sidelobes level. In order to add the contrast improvement to the properties of adaptive beamformers, some techniques like the coherence-based factors and Eigenspace-Based Minimum Variance (ESBMV) are produced in the literature. After demonstrating the principle of Minimum Variance adaptive beamformer, a detailed comparison for the types of coherence-based factors is given. In addition, a new technique of Partial-ESBMV is introduced to modify reference ESBMV so that no Black Box Region artefacts nor dark spots appear when using this method in medical imaging. After explaining its background and properties using cystic and wire phantoms, the proposed method is applied to the real RF data of carotid artery, as an application to clarify the efficiency of this method in medical ultrasound imaging.

The work described in this thesis concentrates on two aspects of Proton NMR imaging: development and evaluation of new/old experimental sequences and application of those techniques to study some non-medical systems that are of industrial importance. Two-dimensional Fourier transform spin warp imaging technique has been evaluated. Importantly, the adaptation of a conventional high resolution spectrometer to perform imaging has been demonstrated with means of "phantoms". This includes calibration of magnetic field gradients, mapping the static magnetic field and radiofrequency field distributions and intensity measurements related to proton spin densities. In addition, a preliminary study describes microscopic imaging of glass capillary tube phantoms containing water. Several different sequences related to Chemical Shift imaging including the one developed during the study have been described. A brief insight into chemical shift artifacts as well as some experimental methods of minimizing some of them have also been presented. The potential of NMR imaging to study non-medical systems has been explored in three different areas of interest: Chromatography columns. Porous rock samples and Wood samples. A variety of NMR imaging sequences have been used to study some interesting and challenging features of these systems which clearly extends the scope of NMR imaging science.
Science, Faculty of
Chemistry, Department of
Graduate

Prostate and breast cancer are the most common cause of cancers in men and women, respectively. Medical imaging plays an important role in breast and prostate cancer detection and evaluation. Then to prove that our web-based medical application could be applied in different medical disciplines, the main part of this thesis is the implementation of two frameworks as a Java applet interface designed as a web-based tool in the domains of mammography from X-rays in radiology, and of prostate imaging from an Magnetic Resonance Imaging (MRI). This aims to facilitate the diagnosis of new mammographic and prostate cases by providing a set of image processing tools that allow a better visualization of the images, and a set of drawing tools used to annotate the suspicious regions (overlays). Each annotation allows including the attributes considered by the experts when issuing the final diagnosis. The overall set of overlays is stored in a database as eXtensible Markup Language (XML) files associated with the original images. Finally, an exhaustive evaluation of the results is also discussed in this thesis. For the application on mammography, the experimental study is performed in order to evaluate the scalability, complexity and response speed at the proposed tool. For the application on MRI of prostate cancer, the evaluation focused on the decrease of the variability of the expert assessments when collaborative work is performed. To conclude, a new architecture with the main goal of managing patient databases with potentially multi-modal imaging is presented such as for an MRI of the prostate cancer and evaluation from potentially several experts.
En aquesta tesi es realitza una revisió bibliogràfica de les principals publicacions recents en els últims anys en aplicacions mèdiques basades en web. Aquest estudi analitza els avantatges i inconvenients dels treballs d’investigació en el camp de la imatge mèdica, així com les arquitectures de base de dades per a la gestió d’imatges digitals. La part principal d’aquesta tesi és la implementació d’una eina basada en la web amb la finalitat de demostrar la integritat i aplicació en diferents disciplines mediques. En aquest sentit, l’aplicació proposada en aquest projecte de tesis ha sigut implementada com a eina d’ajuda al diagnòstic de càncer de mama i pròstata. L’objectiu és facilitar el diagnòstic proporcionant un conjunt d’eines de processat d’imatge que permetin una millor visualització de les imatges, i un conjunt d’eines d’anotació de regions sospitoses o malignes (superposicions). Cada anotació permet incloure tots els atributs i especificacions considerades pels experts a l’emetre el diagnòstic final. S’han dissenyat diferents arquitectures per a la gestió de base de dades (per exemple PACS per emmagatzemar imatges monogràfiques). Per altra banda, el conjunt global d’anotacions s’emmagatzemen en una base de dades d’arxius XML associats a les imatges originals. Conseqüentment, aquesta nova arquitectura es presenta amb l’objectiu d’obtenir una base de dades de casos diagnosticats i validats per radiòlegs experts per a la formació de radiòlegs novells. Finalment, conclusions i noves línies d’investigació associades al projecte com a treball futur són presentades en aquesta tesi.

Medisinsk ultralydavbildning er et relativt rimelig verktøy som er i utstrakte bruk på dagens sykehus og tildels også legekontor. En underliggende antakelse ved dagens avbildningsteknikker er at vevet som skal avbildes i grove trekk er homogent. Det vil i praksis si at de akustiske egenskapene varierer lite. I tilfeller der denne forutsetningen ikke holder vil resultatet bli betraktlig reduksjon av bildekvaliteten. Prosjektet har fokusert på hvordan man best mulig kan korrigere for denne kvalitetsforringelsen. Arbeidet har resultert i et styrket teoretisk rammeverk for modellering, programvare for numerisk simulering. Rammeverket gir en felles forankring for tidligere publiserte metoder som "time-reversal mirror", "beamsum-correlation" og "speckle brightness", og gir derfor en utvidet forståelse av disse metodene. Videre har en ny metode blitt utviklet basert på egenfunksjonsanalyse av et stokastisk tilbakespredt lydfelt. Denne metoden vil potensielt kunne håndtere sterk spredning fra områder utenfor hovedaksen til ultralydstrålen på en bedre måte enn tidligere metoder. Arbeidet er utført ved Institutt for matematiske fag, NTNU, med professor Harald Krogstad, Institutt for matematiske fag, som hovedveileder og professor Bjørn Angelsen, Institutt for sirkulasjon og bildediagnostikk, som medveileder.

Ultra-wideband (UWB) radio techniques have long promised good contrast and high resolution for imaging human tissue and tumours; however, to date, this promise has not entirely been realised. In recent years, microwave imaging has been recognised as a promising non-ionising and non-invasive alternative screening technology, gaining its applicability to breast cancer by the significant contrast in the dielectric properties at microwave frequencies of normal and malignant tissues. This thesis deals with the development of two novel imaging methods based on UWB microwave signals. First, the mode-matching (MM) Bessel-functions-based algorithm, which enables the identification of the presence and location of significant scatterers inside cylindrically-shaped objects is introduced. Next, with the aim of investigating more general 3D problems, the Huygens principle (HP) based procedure is presented. Using HP to forward propagate the waves removes the need to apply matrix generation/inversion. Moreover, HP method provides better performance when compared to conventional time-domain approaches; specifically, the signal to clutter ratio reaches 8 dB, which matches the best figures that have been published. In addition to their simplicity, the two proposed methodologies permit the capture of a minimum dielectric contrast of 1:2, the extent to which different tissues, or differing conditions of tissues, can be discriminated in the final image. Moreover, UWB allows all the information in the frequency domain to be utilised, by combining information gathered from the individual frequencies to construct a consistent image with a resolution of approximately one quarter of the shortest wavelength in the dielectric medium. The power levels used and the specific absorption rates are well within safety limits, while the bandwidths satisfy the UWB definition of being at least 20% of the centre frequencies. It follows that the methodologies permit the detection and location of significant scatterers inside a volume. Validation of the techniques through both simulations and measurements have been performed and presented, illustrating the effectiveness of the methods.

Mestrado em Engenharia de Computadores e Telemática
Nos últimos anos, a imagem médica em formato digital tem sido uma ferramenta cada vez mais importante quer para o diagnóstico médico quer para o auxílio ao tratamento. Assim, equipamentos de aquisição digital e repositórios de imagem médica são cada vez mais comuns em instituições de saúde, podendo até haver mais que um repositório numa instituição. No entanto, esta proliferação de repositórios leva a que a informação esteja dispersa nos vários locais. Esta dispersão da informação juntamente com as diferenças no armazenamento entre instituições são claros obstáculos à pesquisa e acesso integrado a essa informação. Esta dissertação visa o estudo da tecnologia Peer-to-Peer de forma a minimizar os problemas associados à dispersão e heterogeneidade da informação.
In the last years, digital medical imaging has been an increasingly important tool for both medical diagnostic and treatment assistance. Therefore, digital image acquisition equipments and medical imaging repositories are more and more common in a healthcare institution, being possible even more than one repository in one institution. However, this proliferation of repositories leads to dispersion of data between many places. This data dispersion associated with differences in the data storage between institutions are evident obstacles to the search for medical data. This dissertation aims to the study of the Peer-to- Peer technology in order to minimize the problems related to the dispersion and heterogeneity of medical data.

Mestrado em Engenharia de Computadores e Telemática
A imagem médica em formato digital é um elemento presente nas mais variadas instituições prestadoras de cuidados de saúde, afirmando-se como um imprescindível elemento de suporte ao diagnóstico e terapêutica médica. Nesta área, os formatos e processos de armazenamento e transmissão são definidos pela norma internacional DICOM. Um ficheiro deste tipo contempla, para além da imagem (ou vídeo), um conjunto de meta-dados que incluem informação dos pacientes, dados técnicos relativos ao estudo, dose de radiação, relatório clínico, etc. Um dos maiores problemas associados aos repositórios de imagem médica está relacionado com a grande quantidade de dados produzidos que impõe desafios acrescidos ao armazenamento e transporte da informação, em particular em cenários distribuídos e de grande produção de estudos imagiológicos. Esta dissertação tem como objetivo estudar e explorar soluções que permitam a integração do conceito de pertença e controlo de acesso em arquivos de imagem médica, possibilitando a centralização de múltiplas instâncias de arquivos. A solução desenvolvida permite associar permissões a recursos e delegação a terceiras entidades. Foi desenvolvida uma interface programática de gestão da solução proposta, disponibilizada através de web services, com a capacidade de criação, leitura, atualização e remoção de todos os componentes resultantes da arquitetura.
The production of medical images in digital format has been growing in the most varied health care providers, representing at this moment an important and indispensable element for supporting medical decisions. In medical imaging area, the formats and transmission processes are defined by the international DICOM standard. A file in this format contains image pixel data but also a set of metadata, including information about the patient, technical data related to the study, dose of radiation, clinical report, etc. One of the biggest problems associated with medical imaging repositories is related to the large amount of data produced that poses additional challenges to the transport and archive of information, particularly in distributed environments and laboratories with huge volume of examinations. This dissertation aims to study and explore solutions for the integration of ownership concept and access control over medical imaging resources, making possible the centralization of multiple instances of repositories. The proposed solution allows the association of permissions to repository resources and delegation of rights to third entities. It was developed a programmatic interface for management of proposed services, made available through web services, with the ability to create, read, update and remove all components resulting from the architecture.

A "chirp" is a frequency modulated signal widely used in ultrasound imaging to increase the signal-to-noise ratio and penetration depth. In medical ultrasound imaging, resolution and penetration are two major criteria that are inversely proportional. Because of this inverse relation, short duration pulses cannot achieve a high resolution with good penetration. The reasons for this trade-off are the decrease in signal energy due to shorter pulse duration and the attenuation in tissue, which increases with the excitation frequency. The chirp coded excitation however can increase the total transmitted energy using longer pulse durations, while the resolution can be recovered by decoding on receive. Therefore, chirp signals offer potential advantages over single carrier short duration pulses for medical imaging. This work addresses the possible problems encountered in medical ultrasound imaging with chirps and offers new solutions to these problems in terms of signal processing. These proposed solutions are then applied to three major categories of medical ultrasound imaging; hard-tissue ultrasound imaging, soft-tissue ultrasound imaging and contrast-enhanced ultrasound imaging. The application of coded excitation in medical ultrasound imaging is the main motivation behind this work. Therefore, the concepts of frequency modulation and matched filtering are introduced first, and ultrasound specicific problems for pulse compression of chirps are discussed. Examples are given on specific applications and circumstances, where the performance of the traditional pulse compression techniques drops significantly. Alternate methods of pulse compression and filtering of frequency modulated chirps using the Fractional Fourier transform (FrFT) and the Fan Chirp transform (FChT) are presented. Rather than restricting the chirp analysis in the time or frequency domain; these proposed methods transform the signal of interest into a new domain, which is more suitable to analyse frequency modulated chirps.

An important goal in medical imaging is the assessment of image quality in a way that relates to clinical efficacy. An objective approach is to evaluate the performance of diagnosis for specific tasks, using ROC analysis. We shall concentrate here on classification tasks. While many factors may confine the performance achieved for these tasks, we shall investigate two main limiting factors: image blurring and object variability. Psychophysical studies followed by ROC analysis are widely used for system assessment, but it is of great practical interest to be able to predict the outcome of psychophysical studies, especially for system design and optimization. The ideal observer is often chosen as a standard of comparison for the human observer since, at least for simple tasks, its performance can be readily calculated using statistical decision theory. We already know, however, of cases reported in the literature where the human observer performs far below ideal, and one of the purposes of this dissertation is to determine whether there are other practical circumstances where human and ideal performances diverge. Moreover, when the complexity of the task increases, the ideal observer becomes quickly intractable, and other observers such as the Hotelling and the nonprewhitening (npw) ideal observers may be considered instead. A practical problem where our intuition tells us that the ideal observer may fail to predict human performance occurs with imaging devices that are characterized by a PSF having long spatial tails. The investigation of the impact of long-tailed PSFs on detection is of great interest since they are commonly encountered in medical imaging and even more generally in image science. We shall show that the ideal observer is a poor predictor of human performance for a simple two-hypothesis detection task and that linear filtering of the images does indeed help the human observer. Another practical problem of considerable interest is the effect of background nonuniformity on detectability since, it is one more step towards assessing image quality for real clinical images. When the background is known exactly (BKE), the Hotelling and the npw ideal observers predict that detection is optimal for an infinite aperture; a spatially varying background (SVB) results in an optimum aperture size. Moreover, given a fixed aperture size and a BKE, an increase in exposure time is highly beneficial for both observers. For SVB, on the other hand, the Hotelling observer benefits from an increases in exposure time, while the npw ideal observer quickly saturates. In terms of human performance, results show a good agreement with the Hotelling-observer predictions, while the performance disagrees strongly with the npw ideal observer.

Cardiovascular disease is one of the leading causes of the morbidity and mortality in the western world today. Many different imaging modalities are in place today to diagnose and investigate cardiovascular diseases. Each of these, however, has strengths and weaknesses. There are different forms of noise and artifacts in each image modality that combine to make the field of medical image analysis both important and challenging. The aim of this thesis is develop a reliable method for segmentation of vessel structures in medical imaging, combining the expert knowledge of the user in such a way as to maintain efficiency whilst overcoming the inherent noise and artifacts present in the images. We present results from 2D segmentation techniques using different methodologies, before developing 3D techniques for segmenting vessel shape from a series of images. The main drive of the work involves the investigation of medical images obtained using catheter based techniques, namely Intra Vascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT). We will present a robust segmentation paradigm, combining both edge and region information to segment the media-adventitia, and lumenal borders in those modalities respectively. By using a semi-interactive method that utilizes "soft" constraints, allowing imprecise user input which provides a balance between using the user's expert knowledge and efficiency. In the later part of the work, we develop automatic methods for segmenting the walls of lymph vessels. These methods are employed on sequential images in order to obtain data to reconstruct the vessel walls in the region of the lymph valves. We investigated methods to segment the vessel walls both individually and simultaneously, and compared the results both quantitatively and qualitatively in order obtain the most appropriate for the 3D reconstruction of the vessel wall. Lastly, we adapt the semi-interactive method used on vessels earlier into 3D to help segment out the lymph valve. This involved the user interactive method to provide guidance to help segment the boundary of the lymph vessel, then we apply a minimal surface segmentation methodology to provide segmentation of the valve.

xi, 56 p. : ill. (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number.
Image processing is a powerful tool for increasing the reliability and reproducibility of disease diagnostics. In the hands of pathologists, image processing provides quantitative data from histological images which supplement the qualitative data currently used by specialists. This thesis presents a novel method for analyzing digitized images of hematoxylin and eosin (H&E) stained histology slides to detect and quantify inflammatory polymorphonuclear leukocytes to aid in the grading of acute inflammation of the placenta as an example of the use of image processing in aid of diagnostics. Methods presented in this thesis include segmentation, a novel threshold selection technique and shape analysis. The most significant contribution is the automated color threshold selection algorithm for H&E stained histology slides which is the only unsupervised method published to date.
Committee in charge: Dr. John Conery, Chair; Dr. Matthew J. Sottile

L’analyse du mouvement, ou l’analyse d’une séquence d’images, est l’extension naturelle de l’analyse d’images à l’analyse de séries temporelles d’images. De nombreuses méthodes d’analyse de mouvement ont été développées dans le contexte de la vision par ordinateur, incluant le suivi de caractéristiques, le flot optique, l’analyse de points-clef, le recalage d’image, etc. Dans ce manuscrit, nous proposons une boite a outils de techniques d’analyse de mouvement adaptées à l’analyse de séquences biomédicales. Nous avons en particulier travaillé sur les cellules ciliées qui sont couvertes de cils qui battent. Elles sont présentes chez l’homme dans les zones nécessitant des mouvements de fluide. Dans les poumons et les voies respiratoires supérieures, les cils sont responsables de l’épuration muco-ciliaire, qui permet d’évacuer des poumons la poussière et autres impuretés inhalées. Les altérations de l’épuration mucociliaire peuvent être liées à des maladies touchant les cils, pouvant être génétiques ou acquises et peuvent être handicapantes. Ces maladies peuvent être caractérisées par l’analyse du mouvement des cils sous un microscope avec une résolution temporelle importante. Nous avons développé plusieurs outils et techniques pour réaliser ces analyses de manière automatiques et avec une haute précision, à la fois sur des biopsies et in-vivo. Nous avons aussi illustré nos techniques dans le contexte d’éco-toxicité en analysant le rythme cardiaque d’embryons de poissons
Motion analysis, or the analysis of image sequences, is a natural extension of image analysis to time series of images. Many methods for motion analysis have been developed in the context of computer vision, including feature tracking, optical flow, keypoint analysis, image registration, and so on. In this work, we propose a toolbox of motion analysis techniques suitable for biomedical image sequence analysis. We particularly study ciliated cells. These cells are covered with beating cilia. They are present in humans in areas where fluid motion is necessary. In the lungs and the upper respiratory tract, Cilia perform the clearance task, which means cleaning the lungs of dust and other airborne contaminants. Ciliated cells are subject to genetic or acquired diseases that can compromise clearance, and in turn cause problems in their hosts. These diseases can be characterized by studying the motion of cilia under a microscope and at high temporal resolution. We propose a number of novel tools and techniques to perform such analyses automatically and with high precision, both ex-vivo on biopsies, and in-vivo. We also illustrate our techniques in the context of eco-toxicity by analysing the beating pattern of the heart of fish embryo

Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: 3d ultrasound; ultrasound; image processing; image segmentation; 3d image segmentation; medical imaging Includes bibliographical references (p.142-148).

Thesis (M.S. in Management) Naval Postgraduate School, June 1995.
Thesis advisor(s): William R. Gates, John Robert Barrios-Choplin. "June 1995." Bibliography: p. 51-52. Also available online. Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader.

Medical imaging has greatly progressed to become an essential technology in current clinical processes. However, advances in diagnostic imaging have not been applied to the same extent to other fields such as education and meat science. In this thesis two e-learning platforms are presented to improve teaching methodologies in medical and veterinary teaching, focusing mainly in the ease for the content creation and the image interaction, and supporting multiple graphical resources such as 3D models. An image processing algorithm is also presented to improve the quality classification process of farm animals by computing the lean meat percentage, either from carcass or live animals images, proposing for the latter two segmentation algorithms to remove the internal organs
La imatge mèdica ha progressat a bastament per convertir-se en una tecnologia imprescindible en els processos clínics actuals. Tanmateix, els avenços en la imatge per al diagnòstic no s'han aprofitat de la mateixa manera en altres camps com ara l'educació o la ciència de la carn. En aquesta tesi es presenten dues plataformes d'aprenentatge en línia per a millorar els processos d'aprenentatge en la docència mèdica i veterinària, centrant-se sobretot en la facilitat per a la creació de contingut i en la interacció amb la imatge, i donant suport a múltiples recursos gràfics com ara models 3D. També es presenta un algorisme de processament d'imatge per millorar el procés de classificació de la qualitat d'animals de producció calculant el percentatge de carn magra, ja sigui a partir d'imatges de canals o d'animals vius, proposant dos algorismes de segmentació per eliminar els òrgans interns en aquest últim cas

This thesis focuses on Medical Infrared Imaging. It deals with the implementation of an infrared imaging system that can be used as a thermograph. A user interface program is also signed in order to control the imaging system. The system is implemented using Very High Speed Integrated Circuit Description Language (VHDL). Digitizing the data is implemented by Field Programmable Gate Array. Non-uniformities at the detector data are corrected by the two-point correction algorithm. To obtain absolute temperature readings, another system calibration process is also performed. Real-time histogram equalization algorithm and a realtime convolution operation are implemented using the VHDL. Tests of these implementations are performed by comparing the results with the numerical values. A user interface program is developed to allow the operator select any filter type and measure the temperature of any point in the object. Previous studies showed that an infrared system should detect a temperature difference of 500°
mK if it is to be used for biomedical applications. Using a black body system with a precise temperature control, it is shown that this specification is satisfied. Clinical evaluations for a few patients reveal that the implemented medical infrared system can be used for biomedical applications.

This thesis describes methods for reconstruction in non-linear tomography applications. The specific example application in this thesis is Optical Tomography (OT), which seeks the recovery of optical properties such as absorption, scattering and refractive index, given measurements of transmitted light through biological tissue of several centimetres in thickness. Previous methods pose such a problem as the optimisation of a model fitting procedure over a space of piecewise local basis functions such as pixels (or voxels in 3D). We employ a parametrisation of closed surfaces using spherical harmonics based on constrained minimisation of the distortions occurring by the mapping of the surfaces, acquired from voxel images, to a unit sphere. This method could be used to describe parametrically any closed surface, and overcomes the restriction to just star-shaped objects that is commonly found in literature. A surface meshing algorithm is proposed by applying the parametrisation to map regular surface meshes initially defined on the a unit sphere, by tessellation of an embedded icosahedron, upon the parametrically defined surfaces. This procedure creates regular sampled meshes which is a prerequisite for a good discretisation of a surface, in an automatic procedure. A Boundary Element Method for OT is constructed, for the solution of the diffusion equation on realistic geometrical models, constructed from segmented Magnetic Resonance Images (MRI) or Computed Tomography (CT) scans. In this work we propose a method for reconstruction of the boundaries of piecewise constant regions. The shape description for closed surfaces is used in a novel shape estimation inverse problem in 3D using OT measurements, based on a forward solution constructed from BEM and the regular meshes. Some examples are given that portray the capabilities of the proposed method.

Ultrasound is a well-established tool for medical imaging. It is non-invasive and relatively inexpensive, but the severe attenuation caused by propagation through tissue limits its effectiveness for deep imaging. In recent years, the ready availability of fast, inexpensive computer hardware has facilitated the adoption of signal coding and compression techniques to counteract the effects of attenuation. Despite widespread investigation of the topic, published opinions vary as to the relative suitability of discrete-phase-modulated and frequency-modulated (or continuous-phase-modulated) signals for ultrasonic imaging applications. This thesis compares the performance of discrete binary-phase coded pulses to that of frequency-modulated pulses at the higher imaging frequencies at which the effects of attenuation are most severe. The performance of linear and non-linear frequency modulated pulses with optimal side-lobe characteristics is compared to that of complementary binary-phase coded pulses by simulation and experiment. Binary-phase coded pulses are shown to be more robust to the affects of attenuation and non-ideal transducers. The comparatively poor performance of frequency-modulated pulses is explained in terms of the spectral characteristics of the signals and filters required to reduce side-lobes to levels acceptable for imaging purposes. In theory, complementary code sets like bi-phase Golay pairs offer optimum side-lobe performance at the expense of a reduction in frame rate. In practice, misalignment caused by motion in the medium can have a severe impact on imaging performance. A novel motioncompensated imaging algorithm designed to reduce the occurrence of motion artefacts and eliminate the reduction in frame-rate associated with complementary-coding is presented. This is initially applied to conventional sequential-scan B-mode imaging then adapted for use in synthetic aperture B-mode imaging. Simulation results are presented comparing the performance of the motion-compensated sequential-scan and synthetic aperture systems with that of simulated systems using uncoded and frequency-modulated excitation pulses.

This thesis presents a feasibility study of using microwave and millimetre wave radiations to assess burn wounds and the potential for monitoring the healing process under dressing materials, without their removal. As interaction of these types of radiations with the human body is almost exclusively with the skin, there is potential in others areas of medicine such as early skin cancer detection and the diagnosis of skin conditions such as eczema and psoriasis. This study involves developments of experimental methodologies, electromagnetic modelling, and measurements conducted on human skin (in vivo from 150 healthy participants), porcine skin samples (ex vivo from 20 fresh samples), and dressing materials (20 samples). Radiometric measurements obtained from the human skin over the frequency band (80-100) GHz show that the emissivity of the skin varies consistently over different regions of the hand and forearm, with gender, ethnicity, body mass index, age, and hydration level of the skin. A half space electromagnetic model of human skin has been developed and simulations using this model indicate that the human skin can be modelled as a single layer over the band 30 GHz to 300 GHz. The model also indicates that the band could be used to detect burns and a range of medical conditions associated with the skin. Experimental data collected from samples (human and porcine) have been measured by passive and active imaging systems and the results analysed in terms of the emissivity and the reflectivity of the skin. The major outcomes of the thesis are that microwave and millimetre wave radiations are capable of discriminating burn-damaged skin from healthy tissue and these measurements can be made through bandages without the sensor making any physical contact with the skin or the bandage.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student submitted PDF version of thesis.
Includes bibliographical references (p. 144-157).
One of the most versatile and safe materials used in medicine are polymer-coated iron oxide nanoparticles. This dissertation describes several formulations for in vivo imaging applications. The paramagnetic polymer-coated iron oxide nanoparticle aminoSPARK is used as a fluorescence-mediated tomography (FMT) imaging agent for stratification of prostate cancer tumors. This is achieved by conjugating it to a peptide that targets SPARC (secreted protein acidic rich in cysteine), a biomarker protein associated with aggressive forms of prostate cancer. Several types of polymer coatings for iron oxide nanoparticles have been systematically explored using a novel high-throughput screening technique to optimize coating chemistries and synthetic conditions to produce nanoparticles with maximum stability and ability to lower T2 contrast for MR imaging (R2, or relaxivity). Carboxymethyl dextran emerged from the screen as an ideal coating for superparamagnetic iron oxide nanoparticles. A commercially available, FDA-approved nanoparticle with similar surface chemistry, Feraheme, was chosen as a platform nanoparticle for further development. This work presents the first instance of chemical modification of Feraheme, making it more amenable to bioconjugation by converting its free carboxyl groups to free amine groups. This amine-functionalized Feraheme nanoparticle (amino-FH) is then used as a base nanoparticle to which various targeting and reporting functionalities can be added. A FH-based nanoparticle that can be used for cell loading is synthesized by covalently combining Feraheme with protamine, a pharmaceutical that also acts as a membrane translocating agent. A rhodamine-protamine conjugate is synthesized and then covalently bound to amino-FH using carbodiimide (CDI) chemistry. This results in a magnetofluorescent cell-labeling nanoparticle (ProRho-FH) that is readily taken up by mouse mesenchymal stem cells and U87 glioma cells. ProRho-FH can be used to non-invasively track cells for development and monitoring of cell-based therapies or for further investigation of biological mechanisms such as cell migration, tumor growth, and metastasis. This combination of two FDA-approved, commercially available materials to yield a superparamagnetic and fluorescent cell labeling nanoparticle is an excellent alternative to the recently discontinued Feridex. All polymer-coated iron oxide nanoparticles used in this dissertation were thoroughly characterized to fully understand their physicochemical and magnetic properties.
by Suelin Chen.
Ph.D.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 175-184).
Next generation medical imaging technology hinges on the development of cost effective and array compatible transducers making piezoelectric micro-machined ultrasonic transducers (pMUTs) an attractive alternative to the current bulk piezoelectric technology. This thesis aims to realize pMUT potential starting with the development of an effective single cell model that is further scaled to optimize multi-cell elements in a 1D array. In the first half of this work, a transverse mode, lead zirconate titanate (PZT) pMUT plate cell is fabricated using common micro-fabrication techniques and a PZT sol-gel deposition process. Through derivation using a novel Greens function solution technique, an equivalent circuit model with explicitly defined lumped parameters is presented and validated through electrical impedance measurements of fabricated devices and finite element modeling. The equivalent circuit is a crucial design tool as transducer performance metrics, including experimentally validated acoustic domain values, are shown to be defined directly from the lumped parameters. In the second half, figures of merit are identified from these performance metrics and an expanded multi-cell model is employed to strategically target improvements in both bandwidth and coupling while maintaining high pressure output. The resulting, optimized multicell elements in a 1D array are fabricated via a commercially viable, wafer-scale manufacturing process including a novel PZT dry etch. A top-down fabrication approach facilitates achievement of the largest active area of a multi-cell pMUT to date consisting of over 1000 cells in a 200pm x 4mm element footprint, and more substantially, results in the highest electromechanical coupling recorded for a pMUT to date measured at 9 ± 1.4% per element.
by Katherine Marie Smyth.
Ph. D.

Bio-medical imaging is a large umbrella term which covers a number of different imaging modalities used in healthcare today, spanning pre-clinical imaging, to diagnostic imaging and imaging to assist and plan patient treatment. This field of research is pivotal to driving advances in healthcare. This is underpinned by advances in new detector technologies which have the potential to reduce image acquisition time and dose, improving image quality and offer more accurate tools for diagnosis and treatment. Large area CMOS Active Pixel Sensors (APSs) have the potential to deliver these advances in such demanding and continuously evolving field; large imaging area, together with low noise, low cost, fast readout, high dynamic range and potential for in-pixel intelligence have made this technology an ideal candidate to displace currently used imaging technologies in this field. This thesis represents the first investigation into the capabilities of large area CMOS APSs to be used across a number of different imaging modalities in bio-medical science, spanning protein imaging to proton Computed Tomography (CT), using both ionising and non-ionising radiation sources. A novel characterisation of the detector performance has been carried out and set into context of commonly used detectors for bio-medical imaging. Considering the performance parameters assessed for this detector, in comparison with digital detectors commonly used in the clinical practise, this demonstrates how such large area sensor technology may be successfully employed in bio-medical imaging. The novel large area CMOS APS, studied in this work, is proposed as a multi- modality imaging platform for use in pre-clinical science. For the first time direct “contact print” imaging of radioactive and optical labeled biological samples on a large imaging area has been demonstrated, showing its potential application to a broad range of ionising and non-ionising imaging probes. The protein detection capability of this detector has been compared with both film emulsion and commercially available digital systems, demonstrating a higher resolution in protein detection than either film emulsion or a commonly used commercial CCD-based western blotting detection system. Also, when detection capabilities of this imaging system are compared with the state-of-the art devices for tissue autoradiography, this detector system exhibits a sensitivity comparable to that reported for its competitors, whilst offering the largest imaging area. Both these proof of concepts pave the way for large area CMOS APSs to be used as a multi- modality imaging platform in life science. The radiation hardness of a novel large area CMOS APS, designed for medical applications and hardened-by-design, is presented. The radiation damage, produced in this sensor by X-ray and proton irradiation, has been studied as function of total ionising dose and displacement damage dose. The damage contributions from ionising and non-ionising energy deposition have been separated for the proton field and proved independent from proton energy providing a further verification of the Non Ionising Energy Loss (NIEL) scaling hypothesis. The lifetime of this detector for routine use in clinical practice has been evaluated as high as 4 years when used in a typical MegaVolt- age radiotherapy environment, demonstrating how such large area sensor technology may be successfully employed in X-ray and proton based imaging applications. The feasibility of using CMOS APSs as energy-range detectors in proton CT has been demonstrated. Capability of single proton counting, together with potential of energy deposition measurements, have been demonstrated for CMOS APSs. Furthermore, experimental work, based on a simple stack of two CMOS sensors, as well as simulation work has been carried out to prove the capability of such a detection system for pro- ton tracking. Novel algorithms have been developed to perform proton tracking in a CMOS energy-range telescope designed to perform proton CT, paving the way for a new generation of imaging devices to be used in this application.

Mestrado em Engenharia Electrónica e Telecomunicações
A presente dissertação aborda o projecto de um frontend analógico integrado para sincronização e amplificação de sinais produzidos por um fotomultiplicador de silício. A solução proposta pretende possibilitar medidas de tempo com resoluções na ordem dos picosegundos, para implementação em equipamentos compactos dedicados à Tomografia por Emissão de Positrões, com capacidade para medida do tempo de voo de fotões (TOFPET). O canal de frontend completo foi implementado em tecnologia CMOS 130nm, e compreende blocos de préamplificação, integração de carga, equilíbrio dinâmico do ponto de operação, bem como circuitos geradores de correntes de referência, para uma área total em silício de 500x90 μm. A discussão de resultados é baseada em simulações póslayout, e as linhas de investigação futuras são propostas.
An analogue CMOS frontend for triggering and amplification of signals produced by a silicon photomultiplier (SiPM) is proposed. The solution intends to achieve picosecond resolution timing measurements for compact timeofflight Positron Emission Tomography (TOFPET) medical imaging equipments. A 130nm technology was used to implement such frontend, and the design includes preamplification, shaping, baseline holder and biasing circuitry, for a total silicon area of 500x90 μm. Postlayout simulation results are discussed, and ways to optimize the design are proposed.

La plupart des signaux naturels peuvent être représentés par une combinaison linéaire de quelques atomes dans un dictionnaire. Ces représentations parcimonieuses et les méthodes d'apprentissage de dictionnaires (AD) ont suscité un vif intérêt au cours des dernières années. Bien que les méthodes d'AD classiques soient efficaces dans des applications telles que le débruitage d'images, plusieurs méthodes d'AD discriminatifs ont été proposées pour obtenir des dictionnaires mieux adaptés à la classification. Dans ce travail, nous avons montré que la taille des dictionnaires de chaque classe est un facteur crucial dans les applications de reconnaissance des formes lorsqu'il existe des différences de variabilité entre les classes, à la fois dans le cas des dictionnaires classiques et des dictionnaires discriminatifs. Nous avons validé la proposition d'utiliser différentes tailles de dictionnaires, dans une application de vision par ordinateur, la détection des lèvres dans des images de visages, ainsi que par une application médicale plus complexe, la classification des lésions de scléroses en plaques (SEP) dans des images IRM multimodales. Les dictionnaires spécifiques à chaque classe sont appris pour les lésions et les tissus cérébraux sains. La taille du dictionnaire pour chaque classe est adaptée en fonction de la complexité des données. L'algorithme est validé à l'aide de 52 séquences IRM multimodales de 13 patients atteints de SEP
Most natural signals can be approximated by a linear combination of a few atoms in a dictionary. Such sparse representations of signals and dictionary learning (DL) methods have received a special attention over the past few years. While standard DL approaches are effective in applications such as image denoising or compression, several discriminative DL methods have been proposed to achieve better image classification. In this thesis, we have shown that the dictionary size for each class is an important factor in the pattern recognition applications where there exist variability difference between classes, in the case of both the standard and discriminative DL methods. We validated the proposition of using different dictionary size based on complexity of the class data in a computer vision application such as lips detection in face images, followed by more complex medical imaging application such as classification of multiple sclerosis (MS) lesions using MR images. The class specific dictionaries are learned for the lesions and individual healthy brain tissues, and the size of the dictionary for each class is adapted according to the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients

Direct volume rendering (DVR) is a volume visualization technique that has been proved to be a very powerful tool in many scientific visualization domains. Diagnostic medical imaging is one such domain in which DVR provides new capabilities for the analysis of complex cases and improves the efficiency of image interpretation workflows. However, the full potential of DVR in the medical domain has not yet been realized. A major obstacle for a better integration of DVR in the medical domain is the time-consuming process to optimize the rendering parameters that are needed to generate diagnostically relevant visualizations in which the important features that are hidden in image volumes are clearly displayed, such as shape and spatial localization of tumors, its relationship with adjacent structures, and temporal changes in the tumors. In current workflows, clinicians must manually specify the transfer function (TF), view-point (camera), clipping planes, and other visual parameters. Another obstacle for the adoption of DVR to the medical domain is the ever increasing volume of imaging data. The advancement of imaging acquisition techniques has led to a rapid expansion in the size of the data, in the forms of higher resolutions, temporal imaging acquisition to track treatment responses over time, and an increase in the number of imaging modalities that are used for a single procedure. The manual specification of the rendering parameters under these circumstances is very challenging. This thesis proposes a set of innovative methods that visualize important features in multi-dimensional and multi-modality medical images by automatically or semi-automatically optimizing the rendering parameters. Our methods enable visualizations necessary for the diagnostic procedure in which 2D slice of interest (SOI) can be augmented with 3D anatomical contextual information to provide accurate spatial localization of 2D features in the SOI; the rendering parameters are automatically computed to guarantee the visibility of 3D features; and changes in 3D features can be tracked in temporal data under the constraint of consistent contextual information. We also present a method for the efficient computation of visibility histograms (VHs) using adaptive binning, which allows our optimal DVR to be automated and visualized in real-time. We evaluated our methods by producing visualizations for a variety of clinically relevant scenarios and imaging data sets. We also examined the computational performance of our methods for these scenarios.

In many medical imaging modalities, as photons travel from the emission source to the detector, they are scattered by the biological tissue. Often this scatter is viewed as a phenomenon that degrades image quality, and most research is focused on designing methods for either discarding the scattered photons or correcting for scatter. However, the scattered photons also carry information about the tissue that they pass through, which can perhaps be extracted. In this research, we investigate methods to retrieve information from the scattered photons in two specific medical imaging modalities: diffuse optical tomography (DOT) and single photon emission computed tomography (SPECT). To model the scattering of photons in biological tissue, we investigate using the Neumann-series form of the radiative transport equation (RTE). Since the scattering phenomenon are different in DOT and SPECT, the models are individually designed for each modality. In the DOT study, we use the developed photon-propagation model to investigate signal detectability in tissue. To study this detectability, we demonstrate the application of a surrogate figure of merit, based on Fisher information, which approximates the Bayesian ideal observer performance. In the SPECT study, our aim is to determine if only the SPECT emission data acquired in list-mode (LM) format, including the scattered-photon data, can be used to compute the tissue-attenuation map. We first propose a path-based formalism to process scattered photon data, and follow it with deriving expressions for the Fisher information that help determine the information content of LM data. We then derive a maximum-likelihood expectation-maximization algorithm that can jointly reconstruct the activity and attenuation map using LM SPECT emission data. While the DOT study can provide a boost in transition of DOT to clinical imaging, the SPECT study will provide insights on whether it is worth exposing the patient to extra X-ray radiation dose in order to obtain an attenuation map. Finally, although the RTE can be used to model light propagation in tissues, it is computationally intensive and therefore time consuming. To increase the speed of computation in the DOT study, we develop software to implement the RTE on parallel computing architectures, specifically the NVIDIA graphics processing units (GPUs).