Computed tomography (CT) is a widely used medical imaging modality. By rotating an x-ray tube and an x-ray detector around the patient, a CT scanner is able to measure the x-ray transmission from all directions and form an image of the patient’s interior. CT scanners in clinical use today all use energy-integrating detectors, which measure the total incident energy for each measurement interval. A photon-counting detector, on the other hand, counts the number of incoming photons and can in addition measure the energy of each photon by comparing it to a number of energy thresholds. Using photon- counting detectors in computed tomography could lead to improved signal-to-noise ratio, higher spatial resolution and improved spectral imaging which allows better visualization of contrast agents and more reliable quantitative measurements. In this Thesis, the feasibility of using a photon-counting silicon-strip detector for CT is investigated. In the first part of the Thesis, the necessary performance requirements on such a detector is investigated in two different areas: the detector element homogeneity and the capability of handling high photon fluence rates. A metric of inhomogeneity is proposed and used in a simulation study to evaluate different inhomogeneity compensation methods. Also, the photon fluence rate incident on the detector in a scanner in clinical use today is investigated for different patient sizes through dose rate measurements together with simulations of transmission through patient im- ages. In the second part, a prototype detector module is used to demonstrate new applications enabled by the energy resolution of the detector. The ability to generate material-specific images of contrast agents with iodine and gadolinium is demonstrated. Furthermore, it is shown theoretically and ex- perimentally that interfaces in the image can be visualized by imaging the so-called nonlinear partial volume effect. The results suggest that the studied silicon-strip detector is a promising candidate for photon-counting CT.

Nous avons étudié l’utilisation de détecteurs spectrométriques, qui émergent dans le domaine de l’imagerie médicale, pour leur application à la mammographie. Ces détecteurs permettent de discriminer l’énergie des photons reçus, ce qui apporte une information supplémentaire à l’imagerie d’atténuation traditionnelle. Ainsi, il est possible d’utiliser des techniques de décomposition en base de deux matériaux, notamment pour déterminer la densité glandulaire dans le sein, qui correspond au pourcentage de tissus glandulaires, et qui est un facteur de risque pour le développement d’un cancer, à partir d’une seule irradiation. Jusqu’alors, il était possible d’utiliser cette méthode à partir de deux expositions à deux énergies distinctes. Dans certains cas, une nouvelle tendance consiste à pratiquer des mammographies avec injection d’un produit de constratse iodé, mais cela nécessite également au moins deux irradiations. Nous avons donc proposé d’estimer la densité du sein et la concentration d’iode simultanément, à partir d’une seule irradiation, à une dose 0,93 mGy, en appliquant des méthodes de décomposition en base de trois matériaux. Premièrement, des méthodes polynomiales ont été adaptées pour être comptibles avec l’information spectrale provenant de 3 canaux d’énergies. Ensuite, nous avons montré qu’une deuxième approche, capable de prendre en compte une information spectrale plus fine, basée sur la maximisation de la vraisemblance entre un spectre mesuré et des spectres de références, était capable d’atteindre de meilleurs résultats. Enfin, nous avons développé une méthode capable de prendre en compte la compression du sein en mammographie pour améliorer les résultats obtenus par la méthode de maximum de vraisemblance. / Energy sensitive X-ray detectors are emerging in the field of medical imaging. We have investigated the use of this new type of X-ray detectos for their application to mammography exams. These detectors are able to discriminate the energy of received photons, which provides additional information to a standard mammography image only composed of the total attenuation signal. Thus, these detectors allow the use of basis material decomposition techniques, from a single x-ray exposure, and permit to determine the breast density, which corresponds to the percentage of glandular tissues in the breast. Breast density is known for being a risk factor for the development of breast cancers. Without energy sensitive X-ray detectors, this method requires two X-ray exposures at different energies. Contrast enhanced mammography is also developing but it requires the use an iodinated contrast media and at least two irradiations. Hence, we proposed to take benefit of energy-sensitive detectors to simultaneously estimate the breast density and the iodine concentration, using a single X-ray exposure at a mean glandular dose of 0.93 mGy. This approach is based on three basis material decomposition methods. First, different polynomial methods have been adapted to comply with spectral information from 3 energy channels. Then, we showed that a second approach, based on the maximisation of the likelihood between a measured spectrum and reference spectra, was able take into consideration finer spectral information and achieved better results. Finally, we have developed a method that can take into consideration the thickness of the compressed breast during a mammography exam to improve the results obtained by the maximum likelihood method.

La tomographie par rayons X multi-énergétiques (MECT) permet d'obtenir plus d'information concernant la structure interne de l'objet par rapport au scanner CT classique. Un de ses intérêts dans l’imagerie médicale est d'obtenir les images de fractions d’eau et d’os. Dans l'état de l'art, les intérêts de MECT n'est pas encore découvert largement. Les approches de reconstruction existantes sont très limitées dans leurs performances. L'objectif principal de ce travail est de proposer des approches de reconstruction de haute qualité qui pourront être utilisés dans la MECT afin d’améliorer la qualité d’imagerie.Ce travail propose deux approches de reconstruction bayésiennes. La première est adaptée au système avec un détecteur discriminant en énergie. Dans cette approche, nous considérons que les polychromaticités de faisceaux sont négligeables. En utilisant le modèle linéaire de la variance et la méthode d'estimation maximum à postériori (MAP), l'approche que nous avons proposé permets de prendre en compte les différents niveaux de bruit présentés sur les mesures multi-énergétiques. Les résultats des simulations montrent que, dans l'imagerie médicale, les mesures biénergies sont suffisantes pour obtenir les fractions de l'eau et de l'os en utilisant l'approche proposée. Des mesures à la troisième énergie est nécessaire uniquement lorsque l'objet contient des matériaux lourdes. Par exemple, l’acier et l'iode. La deuxième approche est proposée pour les systèmes où les mesures multi-énergétiques sont obtenues avec des faisceaux polychromatiques. C'est effectivement la plupart des cas dans l'état actuel du practice. Cette approche est basée sur un modèle direct non-linéaire et un modèle bruit gaussien où la variance est inconnue. En utilisant l’inférence bayésienne, les fractions de matériaux de base et de la variance d'observation pourraient être estimées à l'aide de l'estimateur conjoint de MAP. Sous réserve à un modèle a priori Dirac attribué à la variance, le problème d'estimation conjointe est transformé en un problème d'optimisation avec une fonction du coût non-quadratique. Pour le résoudre, l'utilisation d'un algorithme de gradient conjugué non-linéaire avec le pas de descente quasi-optimale est proposée.La performance de l'approche proposée est analysée avec des données simulées et expérimentales. Les résultats montrent que l'approche proposée est robuste au bruit et aux matériaux. Par rapport aux approches existantes, l'approche proposée présente des avantages sur la qualité de reconstruction. / Multi-Energy Computed Tomography (MECT) makes it possible to get multiple fractions of basis materials without segmentation. In medical application, one is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical MECT measurements are usually obtained with polychromatic X-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in Beam-Hardening Artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log pre-processing and the water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on non-linear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint Maximum A Posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a non-quadratic cost function. To solve it, the use of a monotone Conjugate Gradient (CG) algorithm with suboptimal descent steps is proposed.The performances of the proposed approach are analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For a variety of materials, less than 5% estimation errors are observed on their average decomposition fractions.The proposed approach is a statistical reconstruction approach based on a non-linear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

Les systèmes d’imagerie par rayons X conventionnels utilisent des détecteurs à base de scintillateur en mode intégration d’énergie. La nouvelle génération de détecteurs à base de semi-conducteur CdTe/CdZnTe permet de compter le nombre de photons et de mesurer l’énergie avec laquelle les photons arrivent sur le détecteur. Le laboratoire LDET (CEA LETI) a développé des détecteurs spectrométriques pixellisés à base de CdTe pour l’imagerie par rayons X associés à un circuit de lecture rapide permettant de travailler à fort taux de comptage avec une bonne résolution en énergie. Ces travaux de thèse proposent d’apporter une contribution au traitement des données acquises sur ces détecteurs résolus en énergie pour la quantification des constituants des matériaux en radiographie et en tomographie. Le cadre médical applicatif choisi est l’ostéodensitométrie. Des simulations de radiographie, qui prennent en compte les imperfections du système de détection, comme le partage de charges et les empilements, ont été réalisées. Nous avons choisi d’étudier des méthodes de traitements des données spectrales basées sur la décomposition en base de matériaux. Cette technique de réduction des données consiste à modéliser le coefficient d’atténuation linéique d’un matériau par une combinaison linéaire des fonctions d’atténuation de deux matériaux de base. Deux approches, utilisant toutes les deux un apprentissage par calibrage, ont été adaptées pour notre application. La première est une adaptation de l’approche polynômiale standard, appliquée pour deux et trois canaux d’énergie. Un processus d’optimisation des seuils des canaux a été réalisé afin de trouver la configuration optimale des bandes d’énergie. Une étude sur le nombre de canaux a permis d’évaluer les limites de la formulation polynômiale. Pour aller plus loin dans l’exploitation du potentiel des nouveaux détecteurs, une approche statistique développée dans notre laboratoire a été adaptée pour la décomposition en base de matériaux. Elle peut se généraliser à un grand nombre de canaux (100 par exemple). Une comparaison des deux approches a été réalisée selon des critères de performance comme le bruit et la précision sur l’estimation des longueurs des matériaux traversés. La validation des deux approches étudiées sur des données expérimentales acquises en radiographie, dans notre laboratoire, avec des détecteurs spectrométriques, a montré une bonne quantification des constituants des matériaux, en accord avec les résultats obtenus en simulation. / Scintillator based integrating detectors are used in conventional X-ray imaging systems. The new generation of energy-resolved semiconductor radiation detectors, based on CdTe/CdZnTe, allows counting the number of photons incident on the detector and measure their energy. The LDET laboratory developed pixelated spectrometric detectors for X-ray imaging, associated with a fast readout circuit, which allows working with high fluxes and while maintaining a good energy resolution. With this thesis, we bring our contribution to data processing acquired in radiographic and tomographic modes for material components quantification. Osteodensitometry was chosen as a medical application. Radiographic data was acquired by simulation with a detector which presents imperfections as charge sharing and pile-up. The methods chosen for data processing are based on a material decomposition approach. Basis material decomposition models the linear attenuation coefficient of a material as a linear combination of the attenuations of two basis materials based on the energy related information acquired in each energy bin. Two approaches based on a calibration step were adapted for our application. The first is the polynomial approach used for standard dual energy acquisitions, which was applied for two and three energies acquired with the energy-resolved detector. We searched the optimal configuration of bins. We evaluated the limits of the polynomial approach with a study on the number of channels. To go further and take benefit of the elevated number of bins acquired with the detectors developed in our laboratory, a statistical approach implemented in our laboratory was adapted for the material decomposition method for quantifying mineral content in bone. The two approaches were compared using figures of merit as bias and noise over the lengths of the materials traversed by X-rays. An experimental radiographic validation of the two approaches was done in our laboratory with a spectrometric detector. Results in material quantification reflect an agreement with the simulations.

A Tomografia Computadorizada de Energia Dupla (DECT em inglês) é um dos campos das imagens tomográficas que mais evoluiu nos últimos anos. O DECT usa dois espectros para irradiar pacientes e é capaz de diferenciar tecidos com base na sua composição elementar. Apesar de serem semelhantes aos dispositivos padrão de tomografia, para essa modalidade é necessário o desenvolvimento de ferramentas específicas que permitam o estudo de suas propriedades de imagem. O objetivo deste trabalho era construir um sistema simulado de Tomografia Computadorizada (TC) com a capacidade de produzir imagens semelhantes às obtidas em dispositivos DECT reais. O TC simulado também permitiria explorar as propriedades das imagens de materiais de teste antes de sua construção física. Este trabalho presenta a simulação do processo de aquisição de imagens de um dispositivo DECT que funciona a partir da troca rápida de kV, o GE Discovery CT 750 HD. A geometria simulada foi baseada num dispositivo atualmente disponível no InRad (Instituto de Radiologia da Faculdade de Medicina da Universidade de São Paulo). As simulações foram realizadas usando o código Monte Carlo PENELOPE/penEasy para simular o transporte de radiação através dos materiais e detectores. Também é apresentada uma comparação entre as imagens obtidas no dispositivo real e nas simulações. Para isso, foi preparado um objeto simulador cilíndrico contendo concentrações de materiais equivalentes a iodo e cálcio. As imagens de tal objeto simulador foram adquiridas no equipamento GE Discovery CT 750 HD. Um objeto simulador equivalente foi modelado e as suas imagens foram simuladas com o código PENELOPE/penEasy. As imagens foram adquiridas e reconstruídas de acordo com as possibilidades do equipamento clínico de tomografia. Imagens de concentração de material e imagens monoenergéticas foram obtidas a partir do dispositivo CT clínico e das simulações. O algoritmo BMD (Basis Material Decomposition em Inglês) baseado nas projeções foi implementado usando os coeficientes de atenuação mássicos da água e do iodo. Consequentemente, imagens de concentração dos materiais água e iodo foram obtidas. A concentração medida nos cilindros de iodo foi equivalente às esperadas tanto no dispositivo real quanto nas imagens simuladas. Foram observados artefatos de endurecimento de feixe nas imagens de concentração de material. Imagens monoenergéticas foram obtidas para diferentes energias. Tais imagens foram obtidas a partir da superposição das imagens de concentração de água e iodo, que foram ponderadas pelos seus respectivos coeficientes de atenuação mássicos. Verificou-se que para as imagens monoenergéticas simuladas e reais em altas energias a imagem de concentração da água é a componente dominante, produzindo imagens que apresentaram as cavidades de iodo como menos atenuantes do que a água. Por outro lado, para energias baixas, a componente dominante nas imagens monoenergéticas foi a imagem de concentração do iodo. O CNR foi analisado nas imagens monoenergéticas como função da energia. As curvas do CNR dos dispositivos simulado e real exibiram semelhanças em sua forma, mas com escala diferente devido à diferença no ruído. Foi possível concluir que o modelo DECT simulado apresenta resultados qualitativos semelhantes aos obtidos no dispositivo real. O sistema de TC simulado permite explorar as características das imagens com diferentes materiais e composições. Ele também pode ser usado como uma ferramenta didática para melhorar a compreensão da diferenciação de materiais em tomografia espectral e DECT. / Dual Energy (DE) Computed Tomography (CT) is one of the fields of tomographic images that has evolved rapidly during the last years. DECT uses two X-ray spectra to irradiate patients It is capable to differentiate materials based on its elementary composition. Despite being similar to standard CT devices, DECT devices require the development of specific tools that allow the study of their image properties. The objective of this work was to build a modelled CT system capable of producing images similar to those obtained in real DECT devices. The modelled CT would also allow exploring the image properties of test materials before their physical construction. This work presents the simulation of the acquisition process of a DECT device that works with rapid kV switching, the GE Discovery CT 750 HD. The simulated geometry was based on a device currently available at the InRad (Institute of Radiology of the Faculty of Medicine of the University of São Paulo). The simulations were carried out using the PENELOPE/penEasy Monte Carlo code, which simulates radiation transport through the materials and detectors. A comparison between the images obtained in the real device and from simulations is also presented. To do so, a real phantom was prepared to be imaged and an equivalent system was simulated. The phantom contained inserts with concentrations of iodine and calcium. The images were acquired and reconstructed according to the possibilities of the real CT device. Standard, material concentration and virtual monoenergetic images were acquired[L1] from both, the real CT device and simulations. The Projection-Based BMD method was implemented using the mass attenuation coefficients of water and iodine. Then, material concentration images of water and iodine were obtained. The iodine concentrations estimated from the images agreed with the expected values in both real device and simulated images. Beam hardening artefacts were observed in the simulated material concentration images. Monoenergetic images were obtained for different energies. Such images were obtained as a superposition of the concentration images of water and iodine, weighed by their respective mass attenuation coefficient. It was verified that in the simulated and real device images, at high energies, the water concentration image predominated in the monoenergetic images, producing images that presented the iodine cavities as less attenuating than water. In contrast, at low energies, the predominant component of the monoenergetic images was the iodine concentration image. Contrast Noise Ratio (CNR) was analysed in the monochromatic images as a function of energy. Simulated and real device CNR curves exhibited similarities in their shape but with a different scale due to their difference in noise. It was possible to conclude that the simulated DECT model presented qualitative results similar to the obtained in the real device. The modelled CT system permits exploring the image features with different materials and compositions. It could also be used as a didactic tool to improve the understanding of material differentiation in spectral or DECT.

A Tomografia Computadorizada de Energia Dupla (DECT em inglês) é um dos campos das imagens tomográficas que mais evoluiu nos últimos anos. O DECT usa dois espectros para irradiar pacientes e é capaz de diferenciar tecidos com base na sua composição elementar. Apesar de serem semelhantes aos dispositivos padrão de tomografia, para essa modalidade é necessário o desenvolvimento de ferramentas específicas que permitam o estudo de suas propriedades de imagem. O objetivo deste trabalho era construir um sistema simulado de Tomografia Computadorizada (TC) com a capacidade de produzir imagens semelhantes às obtidas em dispositivos DECT reais. O TC simulado também permitiria explorar as propriedades das imagens de materiais de teste antes de sua construção física. Este trabalho presenta a simulação do processo de aquisição de imagens de um dispositivo DECT que funciona a partir da troca rápida de kV, o GE Discovery CT 750 HD. A geometria simulada foi baseada num dispositivo atualmente disponível no InRad (Instituto de Radiologia da Faculdade de Medicina da Universidade de São Paulo). As simulações foram realizadas usando o código Monte Carlo PENELOPE/penEasy para simular o transporte de radiação através dos materiais e detectores. Também é apresentada uma comparação entre as imagens obtidas no dispositivo real e nas simulações. Para isso, foi preparado um objeto simulador cilíndrico contendo concentrações de materiais equivalentes a iodo e cálcio. As imagens de tal objeto simulador foram adquiridas no equipamento GE Discovery CT 750 HD. Um objeto simulador equivalente foi modelado e as suas imagens foram simuladas com o código PENELOPE/penEasy. As imagens foram adquiridas e reconstruídas de acordo com as possibilidades do equipamento clínico de tomografia. Imagens de concentração de material e imagens monoenergéticas foram obtidas a partir do dispositivo CT clínico e das simulações. O algoritmo BMD (Basis Material Decomposition em Inglês) baseado nas projeções foi implementado usando os coeficientes de atenuação mássicos da água e do iodo. Consequentemente, imagens de concentração dos materiais água e iodo foram obtidas. A concentração medida nos cilindros de iodo foi equivalente às esperadas tanto no dispositivo real quanto nas imagens simuladas. Foram observados artefatos de endurecimento de feixe nas imagens de concentração de material. Imagens monoenergéticas foram obtidas para diferentes energias. Tais imagens foram obtidas a partir da superposição das imagens de concentração de água e iodo, que foram ponderadas pelos seus respectivos coeficientes de atenuação mássicos. Verificou-se que para as imagens monoenergéticas simuladas e reais em altas energias a imagem de concentração da água é a componente dominante, produzindo imagens que apresentaram as cavidades de iodo como menos atenuantes do que a água. Por outro lado, para energias baixas, a componente dominante nas imagens monoenergéticas foi a imagem de concentração do iodo. O CNR foi analisado nas imagens monoenergéticas como função da energia. As curvas do CNR dos dispositivos simulado e real exibiram semelhanças em sua forma, mas com escala diferente devido à diferença no ruído. Foi possível concluir que o modelo DECT simulado apresenta resultados qualitativos semelhantes aos obtidos no dispositivo real. O sistema de TC simulado permite explorar as características das imagens com diferentes materiais e composições. Ele também pode ser usado como uma ferramenta didática para melhorar a compreensão da diferenciação de materiais em tomografia espectral e DECT. / Dual Energy (DE) Computed Tomography (CT) is one of the fields of tomographic images that has evolved rapidly during the last years. DECT uses two X-ray spectra to irradiate patients It is capable to differentiate materials based on its elementary composition. Despite being similar to standard CT devices, DECT devices require the development of specific tools that allow the study of their image properties. The objective of this work was to build a modelled CT system capable of producing images similar to those obtained in real DECT devices. The modelled CT would also allow exploring the image properties of test materials before their physical construction. This work presents the simulation of the acquisition process of a DECT device that works with rapid kV switching, the GE Discovery CT 750 HD. The simulated geometry was based on a device currently available at the InRad (Institute of Radiology of the Faculty of Medicine of the University of São Paulo). The simulations were carried out using the PENELOPE/penEasy Monte Carlo code, which simulates radiation transport through the materials and detectors. A comparison between the images obtained in the real device and from simulations is also presented. To do so, a real phantom was prepared to be imaged and an equivalent system was simulated. The phantom contained inserts with concentrations of iodine and calcium. The images were acquired and reconstructed according to the possibilities of the real CT device. Standard, material concentration and virtual monoenergetic images were acquired[L1] from both, the real CT device and simulations. The Projection-Based BMD method was implemented using the mass attenuation coefficients of water and iodine. Then, material concentration images of water and iodine were obtained. The iodine concentrations estimated from the images agreed with the expected values in both real device and simulated images. Beam hardening artefacts were observed in the simulated material concentration images. Monoenergetic images were obtained for different energies. Such images were obtained as a superposition of the concentration images of water and iodine, weighed by their respective mass attenuation coefficient. It was verified that in the simulated and real device images, at high energies, the water concentration image predominated in the monoenergetic images, producing images that presented the iodine cavities as less attenuating than water. In contrast, at low energies, the predominant component of the monoenergetic images was the iodine concentration image. Contrast Noise Ratio (CNR) was analysed in the monochromatic images as a function of energy. Simulated and real device CNR curves exhibited similarities in their shape but with a different scale due to their difference in noise. It was possible to conclude that the simulated DECT model presented qualitative results similar to the obtained in the real device. The modelled CT system permits exploring the image features with different materials and compositions. It could also be used as a didactic tool to improve the understanding of material differentiation in spectral or DECT.