A perfilagem de colunas por raios gama (column gamma scan) é uma técnica nuclear empregada para solucionar problemas em equipamentos de processos industriais, nas refinarias e petroquímicas. Consiste na utilização de uma fonte selada e um detector de radiação [NaI(Tl)], obtendo-se o perfil de densidade unidimensional (1D) do equipamento. Nas últimas décadas, ocorreram algumas melhorias na técnica de perfilagem, tais como, na digitalização contínua das informações e nos sistemas de detecção da radiação (wireless). Novos aplicativos melhoraram a qualidade da apresentação dos resultados. Entretanto, a condição da técnica não mudou drasticamente, desde sua criação. Seu resultado é simplesmente um gráfico 1D da densidade média, em função da altura do equipamento industrial. A tecnologia inovadora proposta neste trabalho de Mestrado utiliza a reconstrução tomográfica industrial, via algoritmos iterativos derivados da ART (Algebraic Reconstruction Technique) e do MART (Multiplicative Algebraic Reconstruction Technique), para apresentar o resultado de perfilagem como uma imagem bidimensional (2D) da distribuição de densidade, ao invés de um gráfico 1D. Nitidamente, uma imagem 2D possui mais informações técnicas do equipamento em análise, permitindo um avanço na tecnologia de ensaios não destrutivos (END). Assim, muitos problemas operacionais não detectáveis em equipamentos de processos industriais podem ser descobertos e solucionados de forma on-line, usando-se o imageamento 2D. Esta tecnologia permitiu que um pedido de patente fosse depositado junto ao Instituto Nacional de Propriedade Industrial (INPI). / Column gamma scan is one of the most common nuclear techniques on troubleshooting industrial process equipments like distillation columns and reactors. With a very simple concept, the technique is easy to implement. Searching for a competitive edge the industry has been long developing solutions to achieve better results. On the last decades, significant development has been done with the advent of new hardware, electronics, portable computers and software. Continuous scanning and wireless detection systems are examples of successful field solutions, while new software aid on reporting and data presentation. However the type and quality of the results itself has not dramatically changed since its beginning. A scan profile is simple to understand, although the process to build it can be very complex as it requires a specific blend of knowledge and abilities. Process engineering, chemical engineering, internal hydraulic project, nuclear engineering and field abilities are pre requisites for of any scan specialist. Correct data gathering, interpretation and reporting are abilities often difficult to match or requires a long time of training. The industry faces a similar difficult on the customer side, as it is always necessary to train end users to understand a report and how to use its best. This scientific work describes our effort on developing a new approach on the gamma column scan test using image reconstruction techniques that would result on a graphic image rather than a XY plot. Direct and easier to understand, a report with graphic images would be also be accessible to a wider audience, not limited to the customers experienced with gamma scan interpretation.

Le cancer du sein, l'une des principales causes de mortalité féminine dans le monde, peut être traité avec plus d’efficacité s'il est détecté à un stade précoce. L'imagerie micro-ondes (MWI), technique émergente, apparait comme prometteuse pour compléter les méthodes de diagnostics actuelles. Elle est non-ionisante et potentiellement peu coûteuse, possédant ainsi des caractéristiques clés pour être un bon candidat pour la détection de masse et pour un dépistage fréquent. Cette thèse résume les résultats d'une recherche novatrice menée sur un système micro-onde visant au dépistage dans les tissus mammaires. Une première technique de détection fréquentielle directe est proposée en utilisant une antenne compacte HFA mise en cavité spécifiquement conçue pour une utilisation en contact direct avec le sein. Les résultats de simulations sont analysés et comparés à des mesures faites au CHRU à Brest, ce qui a permis de valider un modèle fantôme dispersif du sein mais aussi de mettre en évidence les limites de cette 1ère technique. Une 2ème approche ULB est proposée dans laquelle une étude de la distribution du champ électrique à l’intérieur du modèle est menée pour deux types d’antennes ULB dédiée à une utilisation en contact direct de la peau, un monopole et une Vivaldi directive, toutes deux insérées dans une cavité. Cette étude comparative a mis en évidence l'intérêt d’utiliser une antenne directive pour cette application. Finalement, une étude élaborée dans le domaine temporel est menée en utilisant deux configurations d’antennes, une configuration mono-statique et une autre bi-statique afin d’étudier la possibilité de la détection tumorale et de la reconstruction d’image. Cette étude permet de justifier la mise au point d’un système antennaire dont l’objectif est de focaliser le maximum d’énergie dans le sein, notamment en concevant les antennes pour une utilisation en contact direct avec la peau pour augmenter la probabilité de la détection des tumeurs cancéreuses. / Breast cancer, one of the primary causes of women mortality worldwide, can be effectively treated if detected at its early stage. Microwave Imaging (MWI), an emerging technique, promises to complement the currently used diagnostic modalities.It is safe, non-ionizing and potentially inexpensive, thus possessing key features to make it a good candidate for frequent and mass screenings.This thesis summarizes the results of an innovative research conducted on a microwave system for breast tissue screening.A first direct frequency detection technique is proposed using a compact HFA antenna inside cavity specifically designed for use in direct contact with the breast. The simulations results are analyzed and compared to measurements made at CHRU of Brest, which validated a dispersive breast phantom model and demonstrated the limits of this first technique.A second UWB approach is proposed in which a study of the electric field distribution inside the model is conducted for two types of UWB antennas dedicated to use in direct skin contact, a monopole and a directive Vivaldi, all two inserted into a cavity.This comparative study has highlighted the interest of using a directional antenna for this application.Finally, the thesis focuses on time domain study using two configurations of antennas, a single-static configuration and another bi-static to study the possibility of tumor detection and image reconstruction and justifying the development of an antenna system whose objective is to focus the maximum energy in the breast to increase the probability of detection.

The problem of reconstructing an image from a set of tomographic data is not new, nor is it lacking attention. However there is still a distinct gap between the mathematicians and the experimental scientists working in the computed tomography (CT) imaging community. One of the aims in this thesis is to bridge this gap with mathematical reconstruction algorithms and analysis approaches applied to practical CT problems. The thesis begins with an extensive analysis for assessing the suitability of reconstruction algorithms for a given problem. The paper presented examines the idea of extracting physical information from a reconstructed sample and comparing against the known sample characteristics to determine the accuracy of a reconstructed volume. Various test cases are studied, which are relevant to both mathematicians and experimental scientists. These include the variance in quality of reconstructed volume as the dose is reduced or the implementation of the level set evolution method, used as part of a simultaneous reconstruction and segmentation technique. The work shows that the assessment of physical attributes results in more accurate conclusions. Furthermore, this approach allows for further analysis into interesting questions in CT. This theme is continued throughout the thesis. Recent results in compressive sensing (CS) gained attention in the CT community as they indicate the possibility of obtaining an accurate reconstruction of a sparse image from severely limited or reduced amount of measured data. Literature produced so far has not shown that CS directly guarantees a successful recovery in X-ray CT, and it is still unclear under which conditions a successful sparsity regularized reconstruction can be achieved. The work presented in the thesis aims to answer this question in a practical setting, and seeks to establish a direct connection between the success of sparsity regularization methods and the sparsity level of the image, which is similar to CS. Using this connection, one can determine the sufficient amount of measurements to collect from just the sparsity of an image. A link was found in a previous study using simulated data, and the work is repeated here with experimental data, where the sparsity level of the scanned object varies. The preliminary work presented here verifies the results from simulated data, showing an "almost-linear" relationship between the sparsity of the image and the sufficient amount of data for a successful sparsity regularized reconstruction. Several unexplained artefacts are noted in the literature as the `partial volume', the 'exponential edge gradient' or the 'penumbra' effect, with no clear explanation for their cause, or established techniques to remove them. The work presented in this paper shows that these artefacts are due to a non-linearity in the measured data, which comes from either the set up of the system, the scattering of rays or the dependency of linear attenuation on wavelength in the polychromatic case. However, even in monochromatic CT systems, the non-linearity effect can be detected. The paper shows that in some cases, the non-linearity effect is too large to ignore, and the reconstruction problem should be adapted to solve a non-linear problem. We derive this non-linear problem and solve it using a numerical optimization technique for both simulatedand real, gamma-ray data. When compared to reconstructions obtained using the standard linear model, the non-linear reconstructed images show clear improvements in that the non-linear effect is largely eliminated. The thesis is finished with a highlight article in the special issue of Solid Earth, named "Pore-scale tomography & imaging - applications, techniques and recommended practice". The paper presents a major technical advancement in a dynamic 3D CT data acquisition, where the latest hardware and optimal data acquisition plan are applied and as a result, ultra fast 3D volume acquisition was made possible. The experiment comprised of fast, free-falling water-saline drops traveling through a pack of rock grains with varying porosities. The imaging work was enhanced by the use of iterative methods and physical quantification analysis performed. The data acquisition and imaging work is the first in the field to capture a free falling drop and the imaging work clearly shows the fluid interaction with speed, gravity and more importantly, the inter- and intra-grain fluid transfers.

In this thesis, Inverse Synthtetic Aperture Radar image reconstruction techniques, named as Range Doppler, Back Projection, Polar Formatting, Multiple Signal Classification (MUSIC) and Time Frequency techniques are analysed and compared using simulations. Time Frequency techniques investigated in this thesis are Short Time Fourier Transform, Wigner-Ville Distribution, Smoothed Wigner-Ville Distribution and Choi-Williams Distribution. First, some fundamental concepts of ISAR, such as resolution, range profile, time dependent Doppler frequency are given. A data simulator is designed and implemented for the purpose of providing configurable input to ISAR signal processing algorithms for a given ISAR target geometry. Estimation of target rotational velocity is explained with the help of three methods, namely Grid Search, WVD Slope and Radon Wigner-Hough Transform. Then, theoretical background of image formation algorithms is discussed. MATLAB simulations for each algorithm are implemented with several configurations in order to visualize and analyse the results. Finally, processing algorithms are compared to discuss the advantages and disadvantages.

<p>Digital tomosynthesis (DTS) is a quasi-three-dimensional (3D) imaging technique which reconstructs images from a limited angle of cone-beam projections with shorter acquisition time, lower imaging dose, and less mechanical constraint than full cone-beam CT (CBCT). However, DTS images reconstructed by the conventional filtered back projection method have low plane-to-plane resolution, and they do not provide full volumetric information for target localization due to the limited angle of the DTS acquisition. </p><p>This dissertation presents the optimization and clinical implementation of image guided radiation therapy using limited-angle projections.</p><p>A hybrid multiresolution rigid-body registration technique was developed to automatically register reference DTS images with on-board DTS images to guide patient positioning in radiation therapy. This hybrid registration technique uses a faster but less accurate static method to achieve an initial registration, followed by a slower but more accurate adaptive method to fine tune the registration. A multiresolution scheme is employed in the registration to further improve the registration accuracy, robustness and efficiency. Normalized mutual information is selected as the criterion for the similarity measure, and the downhill simplex method is used as the search engine. This technique was tested using image data both from an anthropomorphic chest phantom and from head-and-neck cancer patients. The effects of the scan angle and the region-of-interest size on the registration accuracy and robustness were investigated. The average capture ranges in single-axis simulations with a 44° scan angle and a large ROI covering the entire DTS volume were between -31 and +34 deg for rotations and between -89 and +78 mm for translations in the phantom study, and between -38 and +38 deg for rotations and between -58 and +65 mm for translations in the patient study.</p><p>Additionally, a novel limited-angle CBCT estimation method using a deformation field map was developed to optimally estimate volumetric information of organ deformation for soft tissue alignment in image guided radiation therapy. The deformation field map is solved by using prior information, a deformation model, and new projection data. Patients' previous CBCT data are used as the prior information, and the new patient volume to be estimated is considered as a deformation of the prior patient volume. The deformation field is solved by minimizing bending energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. The new patient CBCT volume is then obtained by deforming the prior patient CBCT volume according to the solution to the deformation field. The method was tested for different scan angles in 2D and 3D cases using simulated and real projections of a Shepp-Logan phantom, liver, prostate and head-and-neck patient data. Hardware acceleration and multiresolution scheme are used to accelerate the 3D estimation process. The accuracy of the estimation was evaluated by comparing organ volume, similarity and pixel value differences between limited-angle CBCT and full-rotation CBCT images. Results showed that the respiratory motion in the liver patient, rectum volume change in the prostate patient, and the weight loss and airway volume change in the head-and-neck patient were accurately estimated in the 60° CBCT images. This new estimation method is able to optimally estimate the volumetric information using 60-degree projection images. It is both technically and clinically feasible for image-guidance in radiation therapy.</p> / Dissertation

This thesis explores efficient techniques for generating 3D reconstructions from imagery. Non-linear optimization is one of the core techniques used when computing a reconstruction and is a computational bottleneck for large sets of images. Since non-linear optimization requires a good initialization to avoid getting stuck in local minima, robust systems for generating reconstructions from images build up the reconstruction incrementally. A hierarchical approach is to split up the images into small subsets, reconstruct each subset independently and then hierarchically merge the subsets. Rigidly locking together portions of the reconstructions reduces the number of parameters needed to represent them when merging, thereby lowering the computational cost of the optimization. We present two techniques that involve optimizing with parts of the reconstruction rigidly locked together. In the first, we start by rigidly grouping the cameras and scene features from each of the reconstructions being merged into separate groups. Cameras and scene features are then incrementally unlocked and optimized until the reconstruction is close to the minimum energy. This technique is most effective when the influence of the new measurements is restricted to a small set of parameters. Measurements that stitch together weakly coupled portions of the reconstruction, though, tend to cause deformations in the low error modes of the reconstruction and cannot be efficiently incorporated with the previous technique. To address this, we present a spectral technique for clustering the tightly coupled portions of a reconstruction into rigid groups. Reconstructions partitioned in this manner can closely mimic the poorly conditioned, low error modes, and therefore efficiently incorporate measurements that stitch together weakly coupled portions of the reconstruction. We explain how this technique can be used to scalably and efficiently generate reconstructions from large sets of images.

A number of topics related to Fourier imaging are investigated. Relationships between the magnitude of errors in the amplitude and phase of the Fourier transform of images and the mean square error in reconstructed images are derived. The differing effects of amplitude and phase errors are evaluated, and "equivalent" amplitude and phase errors are derived. A model of the probability density function of the Fourier amplitudes of images is derived. The fundamental basis of phase dominance is studied and quantitated. Inconsistencies in published counter-examples of phase dominance are highlighted. The key characteristics of natural images that lead to their observed power spectral behaviour with spatial frequency are determined.

Seismic layer segmentation, oil-gas boundary surfaces recognition, and 3D volume data reconstruction are three important tasks in three-dimensional seismic image processing. Geophysical and geological parameters and properties have been known to exhibit progressive changes in a layer. However, there are also times when sudden changes can occur between two layers. λ-connectedness was proposed to describe such a phenomenon. Based on graph theory, λ-connectedness describes the relationship among pixels in an image. It is proved that λ-connectedness is an equivalence relation. That is, it can be used to partition an image into different classes and hence can be used to perform image segmentation. Using the random graph theory and λ-connectivity of the image, the length of the path in a λ-connected set can be estimated. In addition to this, the normal λ-connected subsets preserve every path that is λ-connected in the subsets. An O(nlogn) time algorithm is designed for the normal λ-connected segmentation. Techniques developed are used to find objects in 2D/3D seismic images. Finding the interface between two layers or finding the boundary surfaces of an oil-gas reserve is often asked. This is equivalent to finding out whether a λ-connected set is an interface or surface. The problem that is raised is how to recognize a surface in digital spaces. λ-connectedness is a natural and intuitive way for describing digital surfaces and digital manifolds. Fast algorithms are designed to recognize whether an arbitrary set is a digital surface. Furthermore, the classification theorem of simple surface points is deduced: there are only six classes of simple surface points in 3D digital spaces. Our definition has been proved to be equivalent to Morgenthaler-Rosenfeld's definition of digital surfaces in direct adjacency. Reconstruction of a surface and data volume is important to the seismic data processing. Given a set of guiding pixels, the problem of generating a λ-connected (subset of image) surface is an inverted problem of λ-connected segmentation. In order to simplify the fitting algorithm, gradual variation, an equivalent concept of λ-connectedness, is used to preserve the continuity of the fitted surface. The key theorem, the necessary and sufficient condition for the gradually varied interpolation, has been mathematically proven. A random gradually varied surface fitting is designed, and other theoretical aspects are investigated. The concepts are used to successfully reconstruct 3D seismic real data volumes. This thesis proposes λ-connectedness and its applications as applied to seismic data processing. It is used for other problems such as ionogram scaling and object tracking. It has the potential to become a general technique in image processing and computer vision applications. Concepts and knowledge from several areas in mathematics such as Set Theory, Fuzzy Set Theory, Graph Theory, Numerical Analysis, Topology, Discrete Geometry, Computational Complexity, and Algorithm Design and Analysis have been applied to the work of this thesis.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 144-152).

La tomographie optique diffuse (TOD) est une technique d'imagerie médicale émergente utilisant la lumière proche infrarouge pour sonder les tissus biologiques. A partir de mesures non-invasives, cette technique permet d'obtenir les cartes en trois dimensions des coefficients d'absorption et de diffusion à l'intérieur des organes. Avec une approche multi-spectrale, la distribution spatiale des chromophores endogènes (hémoglobine, eau) peut aussi être obtenue. Pour certaines applications cliniques, il est souhaitable d'effectuer les mesures de TOD avec une sonde compacte qui regroupe tous les couples source-détecteur. Cependant, dans cette configuration, la sensibilité en profondeur est un défi majeur. Dans le cadre de cette thèse, nous proposons d'adresser ce challenge en utilisant des mesures résolues en temps. Une approche résolue en temps est développée pour optimiser la TOD dans le cas des mesures de réflectance à faibles distances source-détecteur. Cette approche inclut des aspects méthodologiques concernant le traitement des mesures résolues en temps par des algorithmes de TOD basés sur la transformée de Mellin-Laplace. Cette approche comporte aussi un volet instrumental qui consiste à optimiser la chaîne de détection sur deux points précis pour améliorer la détection et la localisation de contraste d'absorption en profondeur dans les milieux diffusants. Tout d'abord, l'impact de la réponse temporelle du détecteur est étudié avec des détecteurs de photons uniques disponibles dans le commerce (photomultiplicateurs classiques et hybrides). Dans un second temps, l'augmentation de la profondeur sondée avec de nouveaux détecteurs de photons uniques, les fast-gated single-photon avalanche diodes, est explorée au cours d'une collaboration avec le Politecnico de Milan. Pour finir, une étude illustre les performances de l'approche proposée en termes de résolution spatiale en profondeur pour différents arrangements des sources et détecteurs dans une sonde optique. Des sondes optiques dont la largeur est limitée à quelques centimètres ouvrent la voie à de nouvelles applications cliniques pour la TOD. Ces sondes peuvent accéder à des organes internes comme la prostate ou faciliter les examens médicaux sur des organes externes comme le sein ou le cerveau. / Diffuse optical tomography (DOT) is an emerging medical imaging technique using near-infrared light to probe biological tissues. This technique can retrieve three-dimensional maps of absorption and scattering coefficients inside organs from non-invasive measurements. With a multispectral approach, the spatial distribution of endogenous chromophores (hemoglobin, water) can even be obtained. For some clinical applications, it is desirable to carry out the measurements for DOT with a compact probe including all sources and detectors. However, the depth sensitivity is a real challenge in this configuration. We propose to tackle this challenge by using time-resolved measurements. A time-resolved approach is developed to perform DOT with reflectance measurements at short source-detector separation. This approach involves methodological aspects including the processing of time-resolved signals by DOT algorithms based on the Mellin-Laplace transform. Then, this approach consists in optimizing the detection chain on two aspects for enhancing the detection and localization of absorption contrast in depth in diffusive media. First, the impact of the temporal response of the detector is studied with commercially available single-photon detectors (classical and hybrid photomultipliers). Second, the enhancements in probed depth permitted with fast-gated single-photon avalanche diodes are explored in a joint work with the Politecnico di Milano. To finish, a study is carried out to illustrate the performance of the proposed approach with respect to spatial resolution in depth for different configurations of sources and detectors in the optical probe. Probes with a width limited to a few centimeters open the gate to multiple clinical interests. They could access intern organs like the prostate or facilitate the measurements on extern organs like the breast or the brain.