Дисертації з теми "Imaging inverse problems"
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Leung, Wun Ying Valerie. "Inverse problems in astronomical and general imaging." Thesis, University of Canterbury. Electrical and Computer Engineering, 2002. http://hdl.handle.net/10092/7513.
Szasz, Teodora. "Advanced beamforming techniques in ultrasound imaging and the associated inverse problems." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30221/document.
Ultrasound (US) allows non-invasive and ultra-high frame rate imaging procedures at reduced costs. Cardiac, abdominal, fetal, and breast imaging are some of the applications where it is extensively used as diagnostic tool. In a classical US scanning process, short acoustic pulses are transmitted through the region-of-interest of the human body. The backscattered echo signals are then beamformed for creating radiofrequency(RF) lines. Beamforming (BF) plays a key role in US image formation, influencing the resolution and the contrast of final image. The objective of this thesis is to model BF as an inverse problem, relating the raw channel data to the signals to be recovered. The proposed BF framework improves the contrast and the spatial resolution of the US images, compared with the existing BF methods. To begin with, we investigated the existing BF methods in medical US imaging. We briefly review the most common BF techniques, starting with the standard delay-and-sum BF method and emerging to the most known adaptive BF techniques, such as minimum variance BF. Afterwards, we investigated the use of sparse priors in creating original two-dimensional beamforming methods for ultrasound imaging. The proposed approaches detect the strong reflectors from the scanned medium based on the well-known Bayesian Information Criteria used in statistical modeling. Furthermore, we propose a new way of addressing the BF in US imaging, by formulating it as a linear inverse problem relating the reflected echoes to the signal to be recovered. Our approach offers flexibility in the choice of statistical assumptions on the signal to be beamformed and it is robust to a reduced number of pulse emissions. At the end of this research, we investigated the use of the non-Gaussianity properties of the RF signals in the BF process, by assuming alpha-stable statistics of US images
Gregson, James. "Applications of inverse problems in fluids and imaging." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54081.
Science, Faculty of
Computer Science, Department of
Graduate
Lecharlier, Loïc. "Blind inverse imaging with positivity constraints." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209240.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Zhang, Wenlong. "Forward and Inverse Problems Under Uncertainty." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE024/document.
This thesis contains two different subjects. In first part, two cases are considered. One is the thin plate spline smoother model and the other one is the elliptic boundary equations with uncertain boundary data. In this part, stochastic convergences of the finite element methods are proved for each problem.In second part, we provide a mathematical analysis of the linearized inverse problem in multifrequency electrical impedance tomography. We present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor using a novel technique called Diffusion Tensor Magneto-acoustography and propose an optimal control approach for reconstructing the cross-property factor relating the diffusion tensor to the anisotropic electrical conductivity tensor. We prove convergence and Lipschitz type stability of the algorithm and present numerical examples to illustrate its accuracy. The cell model for Electropermeabilization is demonstrated. We study effective parameters in a homogenization model. We demonstrate numerically the sensitivity of these effective parameters to critical microscopic parameters governing electropermeabilization
Zhu, Sha. "A Bayesian Approach for Inverse Problems in Synthetic Aperture Radar Imaging." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00844748.
Alfowzan, Mohammed Fowzan, and Mohammed Fowzan Alfowzan. "Solutions to Space-Time Inverse Problems." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/621791.
Rückert, Nadja. "Studies on two specific inverse problems from imaging and finance." Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-91587.
Som, Subhojit. "Topics in Sparse Inverse Problems and Electron Paramagnetic Resonance Imaging." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1282135281.
Zamanian, Sam Ahmad. "Hierarchical Bayesian approaches to seismic imaging and other geophysical inverse problems." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92970.
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 (pages 189-196).
In many geophysical inverse problems, smoothness assumptions on the underlying geologic model are utilized to mitigate the effects of poor data coverage and observational noise and to improve the quality of the inferred model parameters. In the context of Bayesian inference, these smoothness assumptions take the form of a prior distribution on the model parameters. Conventionally, the regularization parameters defining these assumptions are fixed independently from the data or tuned in an ad hoc manner. However, it is often the case that the smoothness properties of the true earth model are not known a priori, and furthermore, these properties may vary spatially. In the seismic imaging problem, for example, where the objective is to estimate the earth's reflectivity, the reflectivity model is smooth along a particular reflector but exhibits a sharp contrast in the direction orthogonal to the reflector. In such cases, defining a prior using predefined smoothness assumptions may result in posterior estimates of the model that incorrectly smooth out these sharp contrasts. In this thesis, we explore the application of Bayesian inference to different geophysical inverse problems and seek to address issues related to smoothing by appealing to the hierarchical Bayesian framework. We capture the smoothness properties of the prior distribution on the model by defining a Markov random field (MRF) on the set of model parameters and assigning weights to the edges of the underlying graph; we refer to these parameters as the edge strengths of the MRF. We investigate two cases where the smoothing is specified a priori and introduce a method for estimating the edge strengths of the MRF. In the first part of this thesis, we apply a Bayesian inference framework (where the edge strengths of the MRF are predetermined) to the problem of characterizing the fractured nature of a reservoir from seismic data. Our methodology combines different features of the seismic data, particularly P-wave reflection amplitudes and scattering attributes, to allow for estimation of fracture properties under a larger physical regime than would be attainable using only one of these data types. Through this application, we demonstrate the capability of our parameterization of the prior distribution with edge strengths to both enforce smoothness in the estimates of the fracture properties and capture a priori information about geological features in the model (such as a discontinuity that may arise in the presence of a fault). We solve the inference problem via loopy belief propagation to approximate the posterior marginal distributions of the fracture properties, as well as their maximum a posteriori (MAP) and Bayes least squares estimates. In the second part of the thesis, we investigate how the parameters defining the prior distribution are connected to the model covariance and address the question of how to optimize these parameters in the context of the seismic imaging problem. We formulate the seismic imaging problem within the hierarchical Bayesian setting, where the edge strengths are treated as random variables to be inferred from the data, and provide a framework for computing the marginal MAP estimate of the edge strengths by application of the expectation-maximization (E-M) algorithm. We validate our methodology on synthetic datasets arising from 2-D models. The images we obtain after inferring the edge strengths exhibit the desired spatially-varying smoothness properties and yield sharper, more coherent reflectors. In the final part of the thesis, we shift our focus and consider the problem of timelapse seismic processing, where the objective is to detect changes in the subsurface over a period of time using repeated seismic surveys. We focus on the realistic case where the surveys are taken with differing acquisition geometries. In such situations, conventional methods for processing time-lapse data involve inverting surveys separately and subtracting the inversion models to estimate the change in model parameters; however, such methods often perform poorly as they do not correctly account for differing model uncertainty between surveys due to differences in illumination and observational noise. Applying the machinery explored in the previous chapters, we formulate the time-lapse processing problem within the hierarchical Bayesian setting and present a framework for computing the marginal MAP estimate of the time-lapse change model using the E-M algorithm. The results of our inference framework are validated on synthetic data from a 2-D time-lapse seismic imaging example, where the hierarchical Bayesian estimates significantly outperform conventional time-lapse inversion results.
by Sam Ahmad Zamanian.
Ph. D.
Bhandari, Ayush. "Inverse problems in time-of-flight imaging : theory, algorithms and applications." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/95867.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 100-108).
Time-of-Fight (ToF) cameras utilize a combination of phase and amplitude information to return real-time, three dimensional information of a scene in form of depth images. Such cameras have a number of scientific and consumer oriented applications. In this work, we formalize a mathematical framework that leads to unifying perspective on tackling inverse problems that arise in the ToF imaging context. Starting from first principles, we discuss the implications of time and frequency domain sensing of a scene. From a linear systems perspective, this amounts to an operator sampling problem where the operator depends on the physical parameters of a scene or the bio-sample being investigated. Having presented some examples of inverse problems, we discuss detailed solutions that benefit from scene based priors such sparsity and rank constraints. Our theory is corroborated by experiments performed using ToF/Kinect cameras. Applications of this work include multi-bounce light decomposition, ultrafast imaging and fluorophore lifetime estimation.
by Ayush Bhandari.
S.M.
Yin, Ke. "New algorithms for solving inverse source problems in imaging techniques with applications in fluorescence tomography." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/48945.
Wintz, Timothée. "Super-resolution in wave imaging." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE052/document.
Different modalities in wave imaging each present limitations in terms of resolution or contrast. In this work, we present a mathematical model of the ultrafast ultrasound imaging modality and reconstruction methods which can improve contrast and resolution in ultrasonic imaging. We introduce two methods which allow to improve contrast and to locate blood vessels belowthe diffraction limit while simultaneously estimating the blood velocity. We also present a reconstruction method in electrical impedance tomography which allows reconstruction of microscopic parameters from multi-frequency measurements using the theory of homogenization
Hugelier, Siewert. "Approaches to inverse problems in chemical imaging : applications in super-resolution and spectral unmixing." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10144/document.
Besides the chemical information, chemical imaging also offers insights in the spatial distribution of the samples. Within this thesis, we distinguish between two different types of images: spatial-temporal images (super-resolution fluorescence microscopy) and spatial-spectral images (unmixing). In early super-resolution fluorescence microscopy, a low number of fluorophores were active per image. Currently, the field evolves towards high-density imaging that requires new ways of analysis. We propose SPIDER, an image deconvolution approach with multiple penalties. These penalties directly translate the properties of the blinking emitters used in super-resolution fluorescence microscopy imaging. SPIDER allows investigating highly dynamic structural and morphological changes in biological samples with a high fluorophore density. We applied the method on live-cell imaging of a HEK-293T cell labeled with DAKAP-Dronpa and demonstrated a spatial resolution down to 55 nm and a time sampling of 0.5 s. Unmixing hyperspectral images with MCR-ALS provides spatial and spectral information of the individual contributions in the mixture. Due to loss of the pixel neighborhood during the unfolding of the hyperspectral data cube to a two-way matrix, spatial information cannot be added as a constraint during the analysis We therefore propose an alternative approach in which an additional refolding/unfolding step is performed in each iteration. This data manipulation allows global spatial features to be added to the palette of MCR-ALS constraints. From this idea, we also developed several constraints and show their application on experimental data
Hugelier, Siewert. "Approaches to inverse problems in chemical imaging : applications in super-resolution and spectral unmixing." Electronic Thesis or Diss., Lille 1, 2017. http://www.theses.fr/2017LIL10144.
Besides the chemical information, chemical imaging also offers insights in the spatial distribution of the samples. Within this thesis, we distinguish between two different types of images: spatial-temporal images (super-resolution fluorescence microscopy) and spatial-spectral images (unmixing). In early super-resolution fluorescence microscopy, a low number of fluorophores were active per image. Currently, the field evolves towards high-density imaging that requires new ways of analysis. We propose SPIDER, an image deconvolution approach with multiple penalties. These penalties directly translate the properties of the blinking emitters used in super-resolution fluorescence microscopy imaging. SPIDER allows investigating highly dynamic structural and morphological changes in biological samples with a high fluorophore density. We applied the method on live-cell imaging of a HEK-293T cell labeled with DAKAP-Dronpa and demonstrated a spatial resolution down to 55 nm and a time sampling of 0.5 s. Unmixing hyperspectral images with MCR-ALS provides spatial and spectral information of the individual contributions in the mixture. Due to loss of the pixel neighborhood during the unfolding of the hyperspectral data cube to a two-way matrix, spatial information cannot be added as a constraint during the analysis We therefore propose an alternative approach in which an additional refolding/unfolding step is performed in each iteration. This data manipulation allows global spatial features to be added to the palette of MCR-ALS constraints. From this idea, we also developed several constraints and show their application on experimental data
Wei, Hsin-Yu. "Magnetic induction tomography for medical and industrial imaging : hardware and software development." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558901.
GUASTAVINO, SABRINA. "Learning and inverse problems: from theory to solar physics applications." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/998315.
Burvall, Anna. "Axicon imaging by scalar diffraction theory." Doctoral thesis, KTH, Microelectronics and Information Technology, IMIT, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3736.
Axicons are optical elements that produce Bessel beams,i.e., long and narrow focal lines along the optical axis. Thenarrow focus makes them useful ine.g. alignment, harmonicgeneration, and atom trapping, and they are also used toincrease the longitudinal range of applications such astriangulation, light sectioning, and optical coherencetomography. In this thesis, axicons are designed andcharacterized for different kinds of illumination, using thestationary-phase and the communication-modes methods.
The inverse problem of axicon design for partially coherentlight is addressed. A design relation, applicable toSchell-model sources, is derived from the Fresnel diffractionintegral, simplified by the method of stationary phase. Thisapproach both clarifies the old design method for coherentlight, which was derived using energy conservation in raybundles, and extends it to the domain of partial coherence. Thedesign rule applies to light from such multimode emitters aslight-emitting diodes, excimer lasers and some laser diodes,which can be represented as Gaussian Schell-model sources.
Characterization of axicons in coherent, obliqueillumination is performed using the method of stationary phase.It is shown that in inclined illumination the focal shapechanges from the narrow Bessel distribution to a broadasteroid-shaped focus. It is proven that an axicon ofelliptical shape will compensate for this deformation. Theseresults, which are all confirmed both numerically andexperimentally, open possibilities for using axicons inscanning optical systems to increase resolution and depthrange.
Axicons are normally manufactured as refractive cones or ascircular diffractive gratings. They can also be constructedfrom ordinary spherical surfaces, using the sphericalaberration to create the long focal line. In this dissertation,a simple lens axicon consisting of a cemented doublet isdesigned, manufactured, and tested. The advantage of the lensaxicon is that it is easily manufactured.
The longitudinal resolution of the axicon varies. The methodof communication modes, earlier used for analysis ofinformation content for e.g. line or square apertures, isapplied to the axicon geometry and yields an expression for thelongitudinal resolution. The method, which is based on abi-orthogonal expansion of the Green function in the Fresneldiffraction integral, also gives the number of degrees offreedom, or the number of information channels available, forthe axicon geometry.
Keywords:axicons, diffractive optics, coherence,asymptotic methods, communication modes, information content,inverse problems
Alberti, Giovanni S. "On local constraints and regularity of PDE in electromagnetics : applications to hybrid imaging inverse problems." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:1b30b3b7-29b1-410d-ae30-bd0a87c9720b.
Cao, Xiande. "Volume and Surface Integral Equations for Solving Forward and Inverse Scattering Problems." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/65.
Kim, Yong Yook. "Inverse Problems In Structural Damage Identification, Structural Optimization, And Optical Medical Imaging Using Artificial Neural Networks." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11111.
Ph. D.
Nicu, Ana-Maria. "Approximation and representation of functions on the sphere : applications to inverse problems in geodesy and medical imaging." Nice, 2012. http://www.theses.fr/2012NICE4007.
This work concerns the representation and approximation of functions on a sphere with applications to source localization inverse problems in geodesy and medical imaging. The thesis is structured in 6 chapters as follow : Chapter 1 presents an introduction to the geodesy and M/EGG inverse problems. The inverse problem (IP) consists in recovering a density inside the ball (Earth, human brain) from partially known data on the surface. Chapter 2 gives the mathematical background used along the thesis. The resolution of the inverse problem (IP) involves the resolution of two steps : the transmission data problem (TP) and the density recovery (DR) problem. In practice, the data are only available on some region of the sphere, as a spherical cap, like the north hemisphere of the head (M/EGG) or continent (geodesy). For this purpose, in chapter 3, we give an efficient method to build the appropriate Slepian basis on which we express the data. This is set up by using Gauss-Legendre quadrature. The transmission data problem (chapter 4) consists in estimating the data (spherical harmonic expansion) over the whose sphere from noisy measurements expressed in Slepian basis. The second step, density recovery (DR) problem, is detailed in chapter 5 where we study three density models (monopolar, dipolar and inclusions). For the resolution of (DR), we use a best quadratic rational approximation method on planar sections. We give also some properties of the density and the operator which links it to the generated potential. In chapter 6, we study the chapter 3, 4 and 5 from numerical point of view. We present some numerical tests to illustrate source localization results for geodesy and M/EGG problems when we dispose of partial data on the sphere
Hart, Vern Philip II. "The Application of Tomographic Reconstruction Techniques to Ill-Conditioned Inverse Problems in Atmospheric Science and Biomedical Imaging." DigitalCommons@USU, 2012. https://digitalcommons.usu.edu/etd/1354.
Veras, Johann. "Electrical Conductivity Imaging via Boundary Value Problems for the 1-Laplacian." Doctoral diss., University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6377.
Ph.D.
Doctorate
Mathematics
Sciences
Mathematics
Paleo, Pierre. "Méthodes itératives pour la reconstruction tomographique régularisée." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT070/document.
In the last years, there have been a diversification of the tomography imaging technique for many applications. However, experimental constraints often lead to limited data - for example fast scans, or medical imaging where the radiation dose is a primary concern. The data limitation may come as a low signal to noise ratio, scarce views or a missing angle wedge.On the other hand, artefacts are detrimental to reconstruction quality.In these contexts, the standard techniques show their limitations.In this work, we explore how regularized tomographic reconstruction methods can handle these challenges.These methods treat the problem as an inverse problem, and the solution is generally found by the means of an optimization procedure.Implementing regularized reconstruction methods entails to both designing an appropriate regularization, and choosing the best optimization algorithm for the resulting problem.On the modelling part, we focus on three types of regularizers in an unified mathematical framework, along with their efficient implementation: Total Variation, Wavelets and dictionary-based reconstruction. On the algorithmic part, we study which state-of-the-art convex optimization algorithms are best fitted for the problem and parallel architectures (GPU), and propose a new algorithm for an increased convergence speed.We then show how the standard regularization models can be extended to take the usual artefacts into account, namely rings and local tomography artefacts. Notably, a novel quasi-exact local tomography reconstruction method is proposed
Lu, Wei. "Hough transforms for shape identification and applications im medical image processing /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3115568.
Fromenteze, Thomas. "Développement d'une technique de compression passive appliquée à l'imagerie microonde." Thesis, Limoges, 2015. http://www.theses.fr/2015LIMO0061/document.
This work is focused on the development of a compressive technique applied to the simplification of microwave imaging systems. This principle is based on the study of passive devices able to compress transmitted and received waves, allowing for the reduction of the hardware complexity required by radar systems. This approach exploits the modal diversity in the developed components, making it compatible with ultra wide bandwidth. Several proofs of concept are presented using different passive devices, allowing this technique to be adapted to a large variety of architectures and bandwidths
Zeitler, Armin. "Investigation of mm-wave imaging and radar systems." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00832647.
Guerrero, prado Patricio. "Reconstruction tridimensionnelle des objets plats du patrimoine à partir du signal de diffusion inélastique." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLV035/document.
Three-dimensional characterization of flat ancient material objects has remained a challenging activity to accomplish by conventional X-ray tomography methods due to their anisotropic morphology and flattened geometry.To overcome the limitations of such methodologies, an imaging modality based on Compton scattering is studied in this work. Classical X-ray tomography treats Compton scattering data as noise in the image formation process, while in Compton scattering tomography the conditions are set such that Compton data become the principal image contrasting agent. Under these conditions, we are able to avoid relative rotations between the sample and the imaging setup. Mathematically this problem is addressed by means of the conical Radon transform. A model of the direct problem is presented where the output of the system is the spectral image obtained from an input object. The inverse problem is addressed to estimate the 3D distribution of the electronic density of the input object from the spectral image. The feasibility of this methodology is supported by numerical simulations
Henriksson, Tommy. "CONTRIBUTION TO QUANTITATIVE MICROWAVE IMAGING TECHNIQUES FOR BIOMEDICAL APPLICATIONS." Doctoral thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5882.
A dissertation prepared through an international convention for a joint supervision thesis with Université Paris-SUD 11, France
Microwaves in biomedicine
Rückert, Nadja [Verfasser], Bernd [Akademischer Betreuer] Hofmann, Bernd [Gutachter] Hofmann, and Christine [Gutachter] Böckmann. "Studies on two specific inverse problems from imaging and finance / Nadja Rückert ; Gutachter: Bernd Hofmann, Christine Böckmann ; Betreuer: Bernd Hofmann." Chemnitz : Universitätsbibliothek Chemnitz, 2012. http://d-nb.info/1214244068/34.
Gunnarsson, Tommy. "MICROWAVE IMAGING OF BIOLOGICAL TISSUES: applied toward breast tumor detection." Licentiate thesis, Västerås : Department of Computer Science and Electronics, Mälardalen University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-204.
Bendjador, Hanna. "Correction d'aberrations et quantification de vitesse du son en imagerie ultrasonore ultrarapide." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLS011.
Echography relies on the transmission of ultrasound signals through biological tissues, and the processing of backscattered echoes. The rise of ultrafast ultrasound imaging gave access to physiological events faster than 10 000 frames per second. It allowed therefore the development of high-end techniques such as organs elasticity imaging or sensitive quantification of blood flows. During its propagation through complex or heterogeneous media, the acoustic wavefront may still suffer strong distorsions; hindering both the image quality and the ensuing quantitative assessments. Correcting such aberrations is the ultimate goal of the research work conducted during this PhD. By studying statistical properties of interferences between scatterers, a matrix formalism has been developed to optimise the angular coherence of backscattered echoes. Importantly, we succeeded for the first time, in correcting images and quantifying locally the speed of sound at ultrafast frame rates. Sound speed was proven to be a unique biomarker in the example of hepatic steatosis, and possibly separation of brain white and black matter. The phase correction method will be an interesting contribution to motion correction in the case of 3D tomography and vascular imaging, offering thus new horizons to ultrasound imaging
Wörmann, Julian [Verfasser], Martin [Akademischer Betreuer] Kleinsteuber, Martin [Gutachter] Kleinsteuber, and Walter [Gutachter] Stechele. "Structured Co-sparse Analysis Operator Learning for Inverse Problems in Imaging / Julian Wörmann ; Gutachter: Martin Kleinsteuber, Walter Stechele ; Betreuer: Martin Kleinsteuber." München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/1205069437/34.
Salahieh, Basel, Jeffrey J. Rodriguez, Sean Stetson, and Rongguang Liang. "Single-image full-focus reconstruction using depth-based deconvolution." SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 2016. http://hdl.handle.net/10150/624372.
Dekdouk, Bachir. "Image reconstruction of low conductivity material distribution using magnetic induction tomography." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/image-reconstruction-of-low-conductivity-material-distribution-using-magnetic-induction-tomography(44d6769d-59b1-44c2-a01e-835f8916f69c).html.
Mom, Kannara. "Deep learning based phase retrieval for X-ray phase contrast imaging." Electronic Thesis or Diss., Lyon, INSA, 2023. http://www.theses.fr/2023ISAL0087.
The development of highly coherent X-ray sources, such as third-generation synchrotron radiation facilities, has significantly contributed to the advancement of phase contrast imaging. The high degree of coherence of these sources enables efficient implementation of phase contrast techniques, and can increase sensitivity by several orders of magnitude. This novel imaging technique has found applications in a wide range of fields, including material science, paleontology, bone research, medicine, and biology. It enables the imaging of samples with low absorption constituents, where traditional absorption-based methods may fail to provide sufficient contrast. Several phase-sensitive imaging techniques have been developed, among them, propagation-based imaging requires no equipment other than the source, object and detector. Although the intensity can be measured at one or several propagation distances, the phase information is lost and must be estimated from those diffraction patterns, a process called phase retrieval. Phase retrieval in this context is a nonlinear ill-posed inverse problem. Various classical methods have been proposed to retrieve the phase, either by linearizing the problem to obtain an analytical solution, or by iterative algorithms. The main purpose of this thesis was to study what new deep learning approaches could bring to this phase retrieval problem. Various deep learning algorithms have been proposed and evaluated to address this problem. In the first part of this work, we show how neural networks can be used to reconstruct directly from measurements data, without model information. The architecture of the Mixed Scale Dense Network (MS-D Net) is introduced, combining dilated convolution and dense connection. In the second part of this thesis, we propose a nonlinear primal–dual algorithm for the retrieval of phase shift and absorption from a single X-ray in-line phase contrast. We showed that choosing different regularizers for absorption and phase can improve the reconstructions. In the third part, we propose to integrate neural networks into an existing optimization scheme using so-called unrolling approaches, in order to give the convolutional neural networks a specific role in the reconstruction. The performance of theses algorithms are evaluated using simulated noisy data as well as images acquired at NanoMAX (MAX IV, Lund, Sweden)
Ygouf, Marie. "Nouvelle méthode de traitement d'images multispectrales fondée sur un modèle d'instrument pour la haut contraste : application à la détection d'exoplanètes." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00843202.
Zahran, Saeed. "Source localization and connectivity analysis of uterine activity." Thesis, Compiègne, 2018. http://www.theses.fr/2018COMP2469.
The technique of EHGI allows a noninvasive reconstruction of the electrical potential on the uterus surface based on electrical potential measured on the body surface and anatomical data of the torso. EHGI provides very precious information about the uterus condition since it is able to provide refined spatial description of the electrical wave pathway and magnitude on the uterus surface. This may help a lot in different clinical interventions. The scientific algorithms behind any EHGI tool are able to preprocess the anatomical data of the patient in order to provide a computational mesh, filter noisy measurements of the electrical potential and solve an inverse problem. The inverse problem in uterus electrohysterography (electrohysterography imaging (EHGI)) is a new and a powerful diagnosis technique. This non-invasive technology interests more and more medical industries. The success of this technology would be considered as a breakthrough in the uterus diagnosis. However, in many cases the quality of reconstructed electrical potential is not accurate enough. The difficulty comes from the fact that the inverse problem in uterus electrohysterography is well known as a mathematically ill-posed problem. Different methods based on Thikhnov regularization have been used in order to regularize the problem. We have conducted our analysis by using a realistic uterus model and have aimed at identifying the spatial extent of the sources
Shilling, Richard Zethward. "A multi-stack framework in magnetic resonance imaging." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/33807.
Abi, rizk Ralph. "High-resolution hyperspectral reconstruction by inversion of integral field spectroscopy measurements. Application to the MIRI-MRS infrared spectrometer of the James Webb Space Telescope." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG087.
This thesis deals with inverse problem approaches to reconstruct a 3D spatio-spectral image from a set of 2D infrared measurements provided by the Integral Field Spectrometer (IFS) instrument (Mid-Resolution Spectrometer: MRS) of the Mid-Infrared Instrument onboard the James Webb Space Telescope. The reconstruction is challenging because the IFS involves complex components that degrade the measurements: (1) the responses of the components are not perfect and introduce a wavelength-dependent spatial and spectral blurring, (2) the instrument considers several observations of the input with several spatial and spectral fields of views, (3) the output measurements are projected onto multiple 2D detectors and sampled with heterogeneous step sizes. The 3D image reconstruction is an ill-posed problem mainly due to spatio-spectral blurring and insufficient spatial sampling. To compensate for the loss of spatial information, the MRS allows multiple observations of the same scene by shifting the telescope pointing, leading to a multi-frame Super-Resolution (SR) problem. We propose an SR reconstruction algorithm that jointly processes the spatial and spectral information of the degraded 2D measurements following two main steps. First, we design a forward model that describes the response of the IFS instrument as a series of mathematical operators and establishes a relationship between the measurements and the unknown 3D input image. Next, the forward model is used to reconstruct the unknown input.The reconstruction is based on the regularized least square approach with a convex regularization for edge-preserving. We rely on the fast half-quadratic approaches based on Geman and Reynolds formulation to solve the problem. The proposed algorithm mainly includes a fusion step of measurements from different spatio-spectral observations with different blur and different sampling, a multi-frame Super-Resolution step from the different pointing of the instrument, and a deconvolution step to minimize the blurring. Another forward model for the same instrument is also developed in our work, by assuming that the 3D input image lives in a low dimensional subspace and can be modeled as a linear combination of spectral components, assumed known, weighted by unknown mixing coefficients, known as the Linear Mixing Model (LMM). We then rely on the Majorize-Minimize Memory Gradient (3MG) optimization algorithm to estimate the unknown mixing coefficients. The subspace approximation reduces the number of the unknowns. Consequently, the signal-to-noise ratio is increased. In addition, the LMM formulation with known spectral components allows preserving the complex spectral information of the reconstructed 3D image. The proposed reconstruction is tested on several synthetic HS images with different spatial and spectral distributions. Our algorithm shows a clear deconvolution and a significant improvement of the spatial and spectral resolutions of the reconstructed images compared to the state-of-art algorithms, particularly around the edges
Nilsson, Lovisa. "Data-Driven Methods for Sonar Imaging." Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176249.
Irakarama, Modeste. "Towards Reducing Structural Interpretation Uncertainties Using Seismic Data." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0060/document.
Subsurface structural models are routinely used for resource estimation, numerical simulations, and risk management; it is therefore important that subsurface models represent the geometry of geological objects accurately. The first step in building a subsurface model is usually to interpret structural features, such as faults and horizons, from a seismic image; the identified structural features are then used to build a subsurface model using interpolation methods. Subsurface models built this way therefore inherit interpretation uncertainties since a single seismic image often supports multiple structural interpretations. In this manuscript, I study the problem of reducing interpretation uncertainties using seismic data. In particular, I study the problem of using seismic data to determine which structural models are more likely than others in an ensemble of geologically plausible structural models. I refer to this problem as "appraising structural models using seismic data". I introduce and formalize the problem of appraising structural interpretations using seismic data. I propose to solve the problem by generating synthetic data for each structural interpretation and then to compute misfit values for each interpretation; this allows us to rank the different structural interpretations. The main challenge of appraising structural models using seismic data is to propose appropriate data misfit functions. I derive a set of conditions that have to be satisfied by the data misfit function for a successful appraisal of structural models. I argue that since it is not possible to satisfy these conditions using vertical seismic profile (VSP) data, it is not possible to appraise structural interpretations using VSP data in the most general case. The conditions imposed on the data misfit function can in principle be satisfied for surface seismic data. In practice, however, it remains a challenge to propose and compute data misfit functions that satisfy those conditions. I conclude the manuscript by highlighting practical issues of appraising structural interpretations using surface seismic data. I propose a general data misfit function that is made of two main components: (1) a residual operator that computes data residuals, and (2) a projection operator that projects the data residuals from the data-space into the image-domain. This misfit function is therefore localized in space, as it outputs data misfit values in the image-domain. However, I am still unable to propose a practical implementation of this misfit function that satisfies the conditions imposed for a successful appraisal of structural interpretations; this is a subject for further research
Momey, Fabien. "Reconstruction en tomographie dynamique par approche inverse sans compensation de mouvement." Phd thesis, Université Jean Monnet - Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-00842572.
Diouane, Youssef. "Globally convergent evolution strategies with application to Earth imaging problem in geophysics." Phd thesis, Toulouse, INPT, 2014. http://oatao.univ-toulouse.fr/12202/1/Diouane.pdf.
Seifi, Mozhdeh. "Signal processing methods for fast and accurate reconstruction of digital holograms." Phd thesis, Université Jean Monnet - Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-01004605.
Cantalloube, Faustine. "Détection et caractérisation d'exoplanètes dans des images à grand contraste par la résolution de problème inverse." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAY017/document.
Direct imaging of exoplanets provides valuable information about the light they emit, their interactions with their host star environment and their nature. In order to image such objects, advanced data processing tools adapted to the instrument are needed. In particular, the presence of quasi-static speckles in the images, due to optical aberrations distorting the light from the observed star, prevents planetary signals from being distinguished. In this thesis, I present two innovative image processing methods, both based on an inverse problem approach, enabling the disentanglement of the quasi-static speckles from the planetary signals. My work consisted of improving these two algorithms in order to be able to process on-sky images.The first one, called ANDROMEDA, is an algorithm dedicated to point source detection and characterization via a maximum likelihood approach. ANDROMEDA makes use of the temporal diversity provided by the image field rotation during the observation, to recognize the deterministic signature of a rotating companion over the stellar halo. From application of the original version on real data, I have proposed and qualified improvements in order to deal with the non-stable large scale structures due to the adaptative optics residuals and with the remaining level of correlated noise in the data. Once ANDROMEDA became operational on real data, I analyzed its performance and its sensitivity to the user-parameters proving the robustness of the algorithm. I also conducted a detailed comparison to the other algorithms widely used by the exoplanet imaging community today showing that ANDROMEDA is a competitive method with practical advantages. In particular, it is the only method that allows a fully unsupervised detection. By the numerous tests performed on different data set, ANDROMEDA proved its reliability and efficiency to extract companions in a rapid and systematic way (with only one user parameter to be tuned). From these applications, I identified several perspectives whose implementation could significantly improve the performance of the pipeline.The second algorithm, called MEDUSAE, consists in jointly estimating the aberrations (responsible for the speckle field) and the circumstellar objects by relying on a coronagraphic image formation model. MEDUSAE exploits the spectral diversity provided by multispectral data. In order to In order to refine the inversion strategy and probe the most critical parameters, I applied MEDUSAE on a simulated data set generated with the model used in the inversion. To investigate further the impact of the discrepancy between the image model used and the real images, I applied the method on realistic simulated images. At last, I applied MEDUSAE on real data and from the preliminary results obtained, I identified the important input required by the method and proposed leads that could be followed to make this algorithm operational to process on-sky data
Ion, Valentina. "Nonlinear approaches for phase retrieval in the Fresnel region for hard X-ray imaging." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-01015814.
Seppecher, Laurent. "Modélisation de l'imagerie biomédicale hybride par perturbations mécaniques." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2014. http://tel.archives-ouvertes.fr/tel-01021279.
Hadj-Youcef, Mohamed Elamine. "Spatio spectral reconstruction from low resolution multispectral data : application to the Mid-Infrared instrument of the James Webb Space Telescope." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS326/document.
This thesis deals with an inverse problem in astronomy. The objective is to reconstruct a spatio-spectral object, having spatial and spectral distributions, from a set of low-resolution multispectral data taken by the imager MIRI (Mid-InfraRed Instrument), which is on board the next space telescope James Webb Space Telescope (JWST). The observed multispectral data suffers from a spatial blur that varies according to the wavelength due to the spatial convolution with a shift-variant optical response (PSF). In addition the multispectral data also suffers from severe spectral degradations because of the spectral filtering and the integration by the detector over broad bands. The reconstruction of the original object is an ill-posed problem because of the severe lack of spectral information in the multispectral dataset. The difficulty then arises in choosing a representation of the object that allows the reconstruction of this spectral information. A common model used so far considers a spectral shift-invariant PSF per band, which neglects the spectral variation of the PSF. This simplistic model is only suitable for instruments with a narrow spectral band, which is not the case for the imager of MIRI. Our approach consists of developing an inverse problem framework that is summarized in four steps: (1) designing an instrument model that reproduces the observed multispectral data, (2) proposing an adapted model to represent the sought object, (3) exploiting all multispectral dataset jointly, and finally (4) developing a reconstruction method based on regularization methods by enforcing prior information to the solution. The overall reconstruction results obtained on simulated data of the JWST/MIRI imager show a significant increase of spatial and spectral resolutions of the reconstructed object compared to conventional methods. The reconstructed object shows a clear denoising and deconvolution of the multispectral data. We obtained a relative error below 5% at 30 dB, and an execution time of 1 second for the l₂-norm algorithm and 20 seconds (with 50 iterations) for the l₂/l₁-norm algorithm. This is 10 times faster than the iterative solution computed by conjugate gradients