Academic literature 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.