Yes / Dynamic X-ray imaging systems are used for interventional cardiac procedures to treat coronary heart disease. X-ray settings are controlled automatically by specially-designed X-ray dose control mechanisms whose role is to ensure an adequate level of image quality is maintained with an acceptable radiation dose to the patient. Current commonplace dose control designs quantify image quality by performing a simple technical measurement directly from the image. However, the utility of cardiac X-ray images is in their interpretation by a cardiologist during an interventional procedure, rather than in a technical measurement. With the long term goal of devising a clinically-relevant image quality metric for an intelligent dose control system, we aim to investigate the relationship of image noise with clinical professionals’ perception of dynamic image sequences. Computer-generated noise was added, in incremental amounts, to angiograms of five different patients selected to represent the range of adult cardiac patient sizes. A two alternative forced choice staircase experiment was used to determine the amount of noise which can be added to a patient image sequences without changing image quality as perceived by clinical professionals. Twenty-five viewing sessions (five for each patient) were completed by thirteen observers. Results demonstrated scope to increase the noise of cardiac X-ray images by up to 21% ± 8% before it is noticeable by clinical professionals. This indicates a potential for 21% radiation dose reduction since X-ray image noise and radiation dose are directly related; this would be beneficial to both patients and personnel. / This work was funded by Philips Healthcare, NL. Part of this work has been performed in the project PANORAMA, cofunded by grants from Belgium, Italy, France, the Netherlands, and the United Kingdom, and the ENIAC Joint Undertaking.

Esse trabalho apresenta uma nova metodologia para a correção do espectro de potência do ruído no processo de simulação de aquisições de imagens de tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) com doses reduzidas de radiação. A simulação é realizada por meio da inserção de ruído quântico dependente do sinal em imagens previamente adquiridas com a dose padrão de radiação. A DBT utiliza a mesma tecnologia de raios X que a mamografia digital, porém com a capacidade de prover ao médico exames do volume tridimensional da mama, minimizando o problema de superposição de tecidos. Apesar de ser o sucessor da mamografia, estudos têm mostrado que a otimização da relação entre a dose de radiação e a qualidade da imagem adquirida ainda não está bem estabelecida na DBT. Devido à impossibilidade de realizar diversas exposições de radiação a uma mesma paciente para os estudos de otimização da dose de radiação, é desejável que exista um método capaz de simular com exatidão diversas exposições tendo como base uma imagem clínica de referência. Embora existam diversos métodos para a simulação da redução de dose em exames mamográficos, o mesmo não pode ser dito quanto a imagens de DBT. O método desenvolvido para simulação da redução da dose de radiação em imagens de DBT se baseia em uma abordagem de inserção de ruído por meio de uma transformada de estabilização de variância, que já foi utilizada para simulação da redução de dose em exames de mamografia digital. Porém, esse trabalho propõe a inclusão da correção do espectro de potência do ruído para otimizar o desempenho do método de inserção de ruído para exames de DBT. Os resultados obtidos mostraram que, quando comparando a imagens de referência, a as imagens simuladas apresentaram erro menores que 1% para a análise do valor médio e desvio padrão e erro próximo de 5% para a análise do espectro de potência, apresentado resultados até 64% melhores que métodos não otimizados para DBT. / This work presents a new methodology for noise power spectrum correction in the simulation of digital breast tomosynthesis (DBT) images with reduced dose of radiation. The simulation is performed by inserting a signal-dependent quantum noise into previously acquired images with the standard dose of radiation. Using the same X-ray technology as a standard mammography, the DBT is capable of reconstructing the inner tissues of the patients\' breasts as a three-dimensional volume, providing more resources for cancer detection than its bi-dimensional counterpart and minimizing tissue overlapping. Despite being the successor to mammography, studies have shown that the optimization of the relationship between radiation dose and image quality is not well established in DBT yet. Due to the impossibility of exposing the same patient to multiple exams with different doses each, a simulation method able to mimic clinical images with high reliability is desirable. Despite the number of methods proposed for dose reduction simulation in mammography, scarcely any may be used in DBT. The method developed for simulation of radiation dose reduction in DBT images is based on a noise insertion approach using a variance-stabilizing transformation, which has already been used to simulate dose reduction in digital mammography exams. However, this work proposes the inclusion of the noise power spectrum correction to optimize the performance of the noise insertion method for DBT exams. The results showed that, when compared with reference images, the simulated images achieved less than 1% error for mean and standard deviation values and close to 5% error for power spectrum analysis, improving in up to 64% when compared with non-optimized for DBT simulation methods.

In x-ray imaging, the x-ray radiation must be the minimum necessary to achieve the required diagnostic objective, to ensure the patients safety. However, low-dose acquisitions yield images with low quality, which affect the radiologists image interpretation. Therefore, there is a compromise between image quality and radiation dose. This work proposes an image restoration framework capable of restoring low-dose acquisitions to achieve the quality of full-dose acquisitions. The contribution of the new method includes the capability of restoring images with quantum and electronic noise, pixel offset and variable detector gain. To validate the image processing chain, a simulation algorithm was proposed. The simulation generates low-dose DBT projections, starting from fulldose images. To investigate the feasibility of reducing the radiation dose in breast cancer screening programs, a simulated pre-clinical trial was conducted using the simulation and the image processing pipeline proposed in this work. Digital breast tomosynthesis (DBT) images from 72 patients were selected, and 5 human observers were invited for the experiment. The results suggested that a reduction of up to 30% in radiation dose could not be perceived by the human reader after the proposed image processing pipeline was applied. Thus, the image processing algorithm has the potential to decrease radiation levels in DBT, also decreasing the cancer induction risks associated with the exam. / Em programas de rastreamento de câncer de mama, a dose de radiação deve ser mantida o mínimo necessário para se alcançar o diagnóstico, para garantir a segurança dos pacientes. Entretanto, imagens adquiridas com dose de radiação reduzida possuem qualidade inferior. Assim, existe um equilíbrio entre a dose de radiação e a qualidade da imagem. Este trabalho propõe um algoritmo de restauração de imagens capaz de recuperar a qualidade das imagens de tomossíntese digital mamária, adquiridas com doses reduzidas de radiação, para alcançar a qualidade de imagens adquiridas com a dose de referência. As contribuições do trabalho incluem a melhoria do modelo de ruído, e a inclusão das características do detector, como o ganho variável do ruído quântico. Para a validação a cadeia de processamento, um método de simulação de redução de dose de radiação foi proposto. Para investigar a possibilidade de redução de dose de radiação utilizada na tomossíntese, um estudo pré-clínico foi conduzido utilizando o método de simulação proposto e a cadeia de processamento. Imagens clínicas de tomossíntese mamária de 72 pacientes foram selecionadas e cinco observadores foram convidados para participar do estudo. Os resultados sugeriram que, após a utilização do processamento proposto, uma redução de 30% de dose de radiação pôde ser alcançada sem que os observadores percebessem diferença nos níveis de ruído e borramento. Assim, o algoritmo de processamento tem o potencial de reduzir os níveis de radiação na tomossíntese mamária, reduzindo também os riscos de indução do câncer de mama.

Esse trabalho apresenta uma nova metodologia para a correção do espectro de potência do ruído no processo de simulação de aquisições de imagens de tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) com doses reduzidas de radiação. A simulação é realizada por meio da inserção de ruído quântico dependente do sinal em imagens previamente adquiridas com a dose padrão de radiação. A DBT utiliza a mesma tecnologia de raios X que a mamografia digital, porém com a capacidade de prover ao médico exames do volume tridimensional da mama, minimizando o problema de superposição de tecidos. Apesar de ser o sucessor da mamografia, estudos têm mostrado que a otimização da relação entre a dose de radiação e a qualidade da imagem adquirida ainda não está bem estabelecida na DBT. Devido à impossibilidade de realizar diversas exposições de radiação a uma mesma paciente para os estudos de otimização da dose de radiação, é desejável que exista um método capaz de simular com exatidão diversas exposições tendo como base uma imagem clínica de referência. Embora existam diversos métodos para a simulação da redução de dose em exames mamográficos, o mesmo não pode ser dito quanto a imagens de DBT. O método desenvolvido para simulação da redução da dose de radiação em imagens de DBT se baseia em uma abordagem de inserção de ruído por meio de uma transformada de estabilização de variância, que já foi utilizada para simulação da redução de dose em exames de mamografia digital. Porém, esse trabalho propõe a inclusão da correção do espectro de potência do ruído para otimizar o desempenho do método de inserção de ruído para exames de DBT. Os resultados obtidos mostraram que, quando comparando a imagens de referência, a as imagens simuladas apresentaram erro menores que 1% para a análise do valor médio e desvio padrão e erro próximo de 5% para a análise do espectro de potência, apresentado resultados até 64% melhores que métodos não otimizados para DBT. / This work presents a new methodology for noise power spectrum correction in the simulation of digital breast tomosynthesis (DBT) images with reduced dose of radiation. The simulation is performed by inserting a signal-dependent quantum noise into previously acquired images with the standard dose of radiation. Using the same X-ray technology as a standard mammography, the DBT is capable of reconstructing the inner tissues of the patients\' breasts as a three-dimensional volume, providing more resources for cancer detection than its bi-dimensional counterpart and minimizing tissue overlapping. Despite being the successor to mammography, studies have shown that the optimization of the relationship between radiation dose and image quality is not well established in DBT yet. Due to the impossibility of exposing the same patient to multiple exams with different doses each, a simulation method able to mimic clinical images with high reliability is desirable. Despite the number of methods proposed for dose reduction simulation in mammography, scarcely any may be used in DBT. The method developed for simulation of radiation dose reduction in DBT images is based on a noise insertion approach using a variance-stabilizing transformation, which has already been used to simulate dose reduction in digital mammography exams. However, this work proposes the inclusion of the noise power spectrum correction to optimize the performance of the noise insertion method for DBT exams. The results showed that, when compared with reference images, the simulated images achieved less than 1% error for mean and standard deviation values and close to 5% error for power spectrum analysis, improving in up to 64% when compared with non-optimized for DBT simulation methods.

In x-ray imaging, the x-ray radiation must be the minimum necessary to achieve the required diagnostic objective, to ensure the patients safety. However, low-dose acquisitions yield images with low quality, which affect the radiologists image interpretation. Therefore, there is a compromise between image quality and radiation dose. This work proposes an image restoration framework capable of restoring low-dose acquisitions to achieve the quality of full-dose acquisitions. The contribution of the new method includes the capability of restoring images with quantum and electronic noise, pixel offset and variable detector gain. To validate the image processing chain, a simulation algorithm was proposed. The simulation generates low-dose DBT projections, starting from fulldose images. To investigate the feasibility of reducing the radiation dose in breast cancer screening programs, a simulated pre-clinical trial was conducted using the simulation and the image processing pipeline proposed in this work. Digital breast tomosynthesis (DBT) images from 72 patients were selected, and 5 human observers were invited for the experiment. The results suggested that a reduction of up to 30% in radiation dose could not be perceived by the human reader after the proposed image processing pipeline was applied. Thus, the image processing algorithm has the potential to decrease radiation levels in DBT, also decreasing the cancer induction risks associated with the exam. / Em programas de rastreamento de câncer de mama, a dose de radiação deve ser mantida o mínimo necessário para se alcançar o diagnóstico, para garantir a segurança dos pacientes. Entretanto, imagens adquiridas com dose de radiação reduzida possuem qualidade inferior. Assim, existe um equilíbrio entre a dose de radiação e a qualidade da imagem. Este trabalho propõe um algoritmo de restauração de imagens capaz de recuperar a qualidade das imagens de tomossíntese digital mamária, adquiridas com doses reduzidas de radiação, para alcançar a qualidade de imagens adquiridas com a dose de referência. As contribuições do trabalho incluem a melhoria do modelo de ruído, e a inclusão das características do detector, como o ganho variável do ruído quântico. Para a validação a cadeia de processamento, um método de simulação de redução de dose de radiação foi proposto. Para investigar a possibilidade de redução de dose de radiação utilizada na tomossíntese, um estudo pré-clínico foi conduzido utilizando o método de simulação proposto e a cadeia de processamento. Imagens clínicas de tomossíntese mamária de 72 pacientes foram selecionadas e cinco observadores foram convidados para participar do estudo. Os resultados sugeriram que, após a utilização do processamento proposto, uma redução de 30% de dose de radiação pôde ser alcançada sem que os observadores percebessem diferença nos níveis de ruído e borramento. Assim, o algoritmo de processamento tem o potencial de reduzir os níveis de radiação na tomossíntese mamária, reduzindo também os riscos de indução do câncer de mama.

Introduction: Discontinuation of tyrosine kinase inhibitor (TKI) treatment is emerging as the main therapy goal for Chronic Myeloid Leukemia (CML) patients. The DESTINY trial showed that TKI dose reduction prior to cessation can lead to an increased number of patients achieving sustained treatment free remission (TFR). However, there has been no systematic investigation to evaluate how dose reduction regimens can further improve the success of TKI stop trials. Methods: Here, we apply an established mathematical model of CML therapy to investigate different TKI dose reduction schemes prior to therapy cessation and evaluate them with respect to the total amount of drug used and the expected TFR success. Results: Our systematic analysis confirms clinical findings that the overall time of TKI treatment is a major determinant of TFR success, while highlighting that lower dose TKI treatment for the same duration is equally sufficient for many patients. Our results further suggest that a stepwise dose reduction prior to TKI cessation can increase the success rate of TFR, while substantially reducing the amount of administered TKI. Discussion: Our findings illustrate the potential of dose reduction schemes prior to treatment cessation and suggest corresponding and clinically testable strategies that are applicable to many CML patients.

Tesis por compendio / [ES] La prueba médica de Tomografía Computarizada (TC) es esencial actualmente en la práctica clínica para el diagnóstico y seguimiento de múltiples enfermedades y lesiones, siendo una de las pruebas de imagen médica más importante por la gran cantidad de información que es capaz de aportar. Sin embargo, a diferencia de otros métodos de diagnóstico por imagen que son inocuos, la prueba de TC utiliza rayos X, que son ionizantes, por lo que suponen un riesgo para los pacientes. Es por ello que es necesario desarrollar métodos que permitan reducir la dosis de radiación a la que se expone a los pacientes que se realizan un estudio, sin comprometer la calidad de imagen puesto que sino se estaría sometiendo a un riesgo a estas personas sin que un diagnóstico de calidad esté garantizado. Durante el desarrollo de esta tesis se han investigado métodos de reconstrucción de imagen TC que se basan en reducir el número de proyecciones usadas, con el objetivo de reducir el tiempo de exposición a los rayos X. Esta estrategia de reducción de dosis está en fase de investigación, a diferencia de otras que están implantadas en la práctica clínica y ya han sido desarrolladas por los propios fabricantes de los escáneres. Por tanto, nos hemos centrado en los llamados métodos algebraicos de reconstrucción, que son los más apropiados para este tipo de adquisición de proyecciones puesto que son capaces de trabajar con menos información que los métodos clásicos conservando una buena calidad de imagen. En concreto, se ha estudiado a fondo el comportamiento del método LSQR para la resolución de este problema, combinado con una técnica de filtrado llamada Soft Thresholding Filter y una técnica de aceleración llamada FISTA. Además, se ha introducido el filtro de imagen Bilateral que es capaz de mejorar la calidad de las imágenes cuando se combina con los métodos anteriores. El estudio multiparamétrico realizado se ha llevado a cabo en un entorno de computación distribuida Grid, para analizar cómo los distintos parámetros que intervienen en el proceso de reconstrucción pueden influir sobre la imagen resultado. Dicho estudio se ha diseñado para hacer uso de la potencia de cómputo de la plataforma distribuida aunque el software que se necesita no esté disponible. La instalación de dicho software se puede realizar en el tiempo de ejecución de los trabajos, o en se puede empaquetar en una imagen que estará instalada en un contenedor Docker, lo que es una opción muy interesante para sistemas donde no tengamos privilegios. El esquema seguido para la creación y lanzamiento de los trabajos es fácilmente reproducible. Por otra parte, se han planteado dos métodos algebraicos directos para la reconstrucción de TC basados en la factorización de la matriz que modela el sistema. El primero es el método SVD, que se ha probado mediante la librería SLEPc, obteniendo mayores tasas de uso de memoria principal, por lo que ha sido descartado en favor del método QR. La primera aproximación a la resolución se ha hecho mediante la librería SuiteSparseQR, desarrollando después un método propio siguiendo la técnica Out-Of-Core que permite almacenar las matrices en el propio disco duro en lugar de cargarlas en memoria, por lo que el tamaño del problema puede aumentar sin que el coste del hardware sea muy alto. Dicho método obtiene reconstrucciones de alta calidad cuando el rango de la matriz factorizada es completo. En los resultados se muestra como para una resolución alta, garantizar el rango completo todavía supone una reducción del número de proyecciones con respecto a métodos tradicionales. Por tanto, en esta tesis se ha llevado a cabo la investigación y el posterior desarrollo mediante librerías y técnicas de computación de Altas Prestaciones de varios métodos algebraicos de reconstrucción de TC basados en la reducción de proyecciones que permiten mantener una buena calidad de imagen. Dichos métodos han sido optimizados para lograr los menores tiempos de reconstrucción posibles, con el fin de hacerlos competitivos y que algún día puedan ser instaurados en la práctica clínica. / [CA] Actualment, la prova mèdica de tomografia computeritzada (TC) és essencial en la pràctica clínica per al diagnòstic i el seguiment de múltiples malalties i lesions, sent una de les proves d'imatge mèdica més importants a causa de la gran quantitat d'informació que és capaç d'oferir. Tanmateix, a diferència d'altres mètodes d'imatge médica, la prova CT utilitza raigs X, que són ionitzants i suposen un risc per als pacients. Per això, és necessari desenvolupar mètodes que permetin reduir la dosi de radiació a la qual estan exposats els pacients sotmesos a un estudi, sense comprometre la qualitat de la imatge, ja que en cas contrari estarien sotmetent a aquestes persones a un risc sense que es garantís l'avantatge d'un diagnòstic d'alta qualitat. Durant el desenvolupament d'aquesta tesi, s'han investigat diversos mètodes de reconstrucció d'imatges CT basats en la reducció del nombre de projeccions utilitzades, amb l'objectiu de reduir el temps d'exposició als raigs X. Aquesta estratègia de reducció de dosis es troba en fase investigació, a diferència d'altres que s'implementen a la pràctica clínica i que ja han estat desenvolupades pels propis fabricants d'escàners. Per tant, ens hem centrat en els anomenats mètodes de reconstrucció algebraica, que són els més adequats per a aquest tipus d'adquisició de projecció, ja que són capaços de treballar amb menys informació que els mètodes clàssics mantenint una bona qualitat d'imatge. Concretament, s'ha estudiat a fons el comportament del mètode LSQR per resoldre aquest problema, combinat amb una tècnica de filtratge anomenada Soft Thresholding Filter i una tècnica d'acceleració anomenada FISTA. A més, s'ha introduït un filtre d'imatges anomenat filtre bilateral, que és capaç de millorar la qualitat de les imatges quan es combina amb els mètodes anteriors. L'estudi multiparamètric de LSQR es va dur a terme en un entorn informàtic distribuït Grid, per analitzar com els diferents paràmetres implicats en el procés de reconstrucció poden influir en la imatge resultant. Aquest estudi ha estat dissenyat per fer ús de la potència de càlcul de la plataforma distribuïda encara que el programari requerit no estigui disponible. La instal·lació d'aquest programari es pot fer en el moment d'executar els treballs o es pot empaquetar en una imatge que s'instal·larà en un contenidor Docker, que és una opció molt interessant per a sistemes on no tenim privilegis. L'esquema seguit per a la creació i el llançament dels treballs es pot reproduir fàcilment per a estudis multiparamètrics d'aquest tipus. D'altra banda, s'han proposat dos mètodes algebraics directes per a la reconstrucció CT basats en la factorització de la matriu que modela el sistema. El primer és el mètode SVD, que s'ha provat mitjançant la biblioteca SLEPc, obtenint taxes d'ús més alt de memòria principal, motiu pel qual s'ha descartat a favor del mètode QR. La primera aproximació a la resolució s'ha fet a través de la biblioteca SuiteSparseQR, desenvolupant posteriorment la nostra pròpia implementació mitjançant la tècnica Out-Of-Core que permet emmagatzemar les matrius al disc dur en lloc de carregar-les a la memòria, de manera que la mida de el problema pot augmentar sense que el cost del maquinari sigui molt alt. Aquest mètode obté reconstruccions d'alta qualitat quan el rang de la matriu factoritzada és complet. En els resultats es demostra que per a una alta resolució, garantir el rang complet encara significa una reducció del nombre de projeccions en comparació amb els mètodes tradicionals. Per tant, en aquesta tesi s'ha dut a terme la investigació i el desenvolupament posterior de diversos mètodes de reconstrucció algebraica de CT mitjançant biblioteques i tècniques de computació d'altes prestacions. Aquests mètodes basats en la reducció de projeccions, que permeten mantenir una bona qualitat d’imatge, s’han optimitzat per aconseguir els temps de reconstrucció més breus possibles, per tal de fer-los competitius perquè algun dia puguin implementarse a la pràctica clínica. / [EN] The Computerized Tomography (CT) medical test is currently essential in clinical practice for the diagnosis and monitoring of multiple diseases and injuries, being one of the most important medical imaging tests due to the large amount of information it is capable of providing. However, unlike other safe imaging methods, the CT test uses X-rays, which are ionizing, posing a risk to patients. That is why it is necessary to develop methods that allow reducing the radiation dose to which patients undergoing a study are exposed, without compromising image quality since otherwise they would be subjecting these people to a risk without the benefit of a high-quality diagnosis being guaranteed. During the development of this thesis, several CT image reconstruction methods that are based on reducing the number of projections used have been investigated, with the aim of reducing the time of exposure to X-rays. This dose reduction strategy is in research phase, unlike others that are implemented in clinical practice and have already been developed by the scanner manufacturers themselves. Therefore, we have focused on the algebraic reconstruction methods, which are the most appropriate for this type of projection acquisition since they are capable of working with less information than the classical methods while maintaining good image quality. Specifically, the behavior of the LSQR method to solve this problem has been thoroughly studied, combined with a filtering technique called Soft Thresholding Filter and an acceleration technique called FISTA. In addition, the so-called Bilateral filter has been introduced, which is capable of improving the quality of images when combined with the above methods. The multiparametric LSQR study was carried out in a Grid distributed computing environment, to analyze how the different parameters involved in the reconstruction process can influence the resulting image. This study has been designed to make use of the computing power of the distributed platform even if the software required is not available. The installation of said software can be done at the time of execution of the jobs, or it can be packaged in an image that will be installed in a Docker container, which is a very interesting option for systems where we do not have privileges. The scheme followed for the creation and launch of the jobs is easily reproducible for multiparametric studies of this type. On the other hand, two direct algebraic methods have been proposed for CT reconstruction based on the factorization of the matrix that models the system. The first is the SVD method, which has been tested using the SLEPc library, obtaining higher rates of main memory usage, which is why it has been discarded in favor of the QR method. The first approximation to the resolution has been made through the SuiteSparseQR library, later developing our own implementation using the Out-Of-Core technique that allows the matrices to be stored on the hard drive itself instead of loading them in memory, so the size of the problem can increase without the cost of the hardware being very high. This method obtains high-quality reconstructions when the rank of the factored matrix is complete. In the results it is shown that for a high resolution, guaranteeing the full rank still means a reduction in the number of projections compared to traditional methods. Therefore, in this thesis, research and subsequent development of several algebraic CT reconstruction methods has been carried out using libraries and High Performance Computing techniques. These methods based on the reduction of projections, which allows maintaining good image quality, and have been optimized to achieve the shortest possible reconstruction times, in order to make them competitive so that one day they can be implemented in clinical practice. / This research has been supported by Universitat Politècnica de València and partially funded by TIN2015-66972-C5-4-R, ENE2014-59442-P-AR and TIN2013-44390-R projects of the "Ministerio de Economía y Competitividad" of Spain, as well as the Spanish ”Generalitat Valenciana” PROMETEOII/2014/008, PROMETEO/2018/035 projects and ACIF/2017/075 predoctoral grant. This work has also been co-financed by FEDER and FSE funds, and the “Spanish Ministry of Science, Innovation and Universities” under Grant RTI2018-098156-B-C54 / Chillarón Pérez, M. (2021). Análisis y desarrollo de algoritmos de altas prestaciones para reconstrucción de imagen médica TAC 3D basados en la reducción de dosis [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/180116 / Compendio

Cette thèse est constituée de deux principaux axes de recherche portant sur l'imagerie dentaire par la tomographie à rayons X : le développement de nouvelles méthodes itératives de reconstruction tomographique afin de réduire les artefacts métalliques et la réduction de la dose délivrée au patient. Afin de réduire les artefacts métalliques, nous prendrons en compte le durcissement du spectre des faisceaux de rayons X et le rayonnement diffusé. La réduction de la dose est abordée dans cette thèse en diminuant le nombre des projections traitées. La tomographie par rayons X a pour objectif de reconstruire la cartographie des coefficients d'atténuations d'un objet inconnu de façon non destructive. Les bases mathématiques de la tomographie repose sur la transformée de Radon et son inversion. Néanmoins des artefacts métalliques apparaissent dans les images reconstruites en inversant la transformée de Radon (la méthode de rétro-projection filtrée), un certain nombre d'hypothèse faites dans cette approche ne sont pas vérifiées. En effet, la présence de métaux exacerbe les phénomènes de durcissement de spectre et l'absence de prise en compte du rayonnement diffusé. Nous nous intéressons dans cette thèse aux méthodes itératives issues d'une méthodologie Bayésienne. Afin d'obtenir des résultats de traitement compatible avec une application clinique de nos nouvelles approches, nous avons choisi un modèle direct relativement simple et classique (linéaire) associé à des approches de corrections de données. De plus, nous avons pris en compte l'incertitude liée à la correction des données en utilisant la minimisation d'un critère de moindres carrés pondérés. Nous proposons donc une nouvelle méthode de correction du durcissement du métal sans connaissances du spectre de la source et des coefficients d'atténuation des matériaux. Nous proposons également une nouvelle méthode de correction du diffusé associée sur les mesures sous certaines conditions notamment de faible dose. En imagerie médicale par tomographie à rayons X, la surexposition ou exposition non nécessaire irradiante augmente le risque de cancer radio-induit lors d'un examen du patient. Notre deuxième axe de recherche porte donc sur la réduction de la dose en diminuant le nombre de projections. Nous avons donc introduit un nouveau mode d'acquisition possédant un échantillonnage angulaire adaptatif. On utilise pour définir cette acquisition notre connaissance a priori de l'objet. Ce mode d'acquisition associé à un algorithme de reconstruction dédié, nous permet de réduire le nombre de projections tout en obtenant une qualité de reconstruction comparable au mode d'acquisition classique. Enfin, dans certains modes d’acquisition des scanners dentaires, nous avons un détecteur qui n'arrive pas à couvrir l'ensemble de l'objet. Pour s'affranchir aux problèmes liés à la tomographie locale qui se pose alors, nous utilisons des acquisitions multiples suivant des trajectoires circulaires. Nous avons adaptés les résultats développés par l’approche « super short scan » [Noo et al 2003] à cette trajectoire très particulière et au fait que le détecteur mesure uniquement des projections tronquées. Nous avons évalué nos méthodes de réduction des artefacts métalliques et de réduction de la dose en diminuant le nombre des projections sur les données réelles. Grâce à nos méthodes de réduction des artefacts métalliques, l'amélioration de qualité des images est indéniable et il n'y a pas d'introduction de nouveaux artefacts en comparant avec la méthode de l'état de l'art NMAR [Meyer et al 2010]. Par ailleurs, nous avons réussi à réduire le nombre des projections avec notre nouveau mode d'acquisition basé sur un « super short scan » appliqué à des trajectoires multiples. La qualité obtenue est comparable aux reconstructions obtenues avec les modes d'acquisition classiques ou short-scan mais avec une réduction d’au moins 20% de la dose radioactive. / This thesis contains two main themes: development of new iterative approaches for metal artifact reduction (MAR) and dose reduction in dental CT (Computed Tomography). The metal artifacts are mainly due to the beam-hardening, scatter and photon starvation in case of metal in contrast background like metallic dental implants in teeth. The first issue concerns about data correction on account of these effects. The second one involves the radiation dose reduction delivered to a patient by decreasing the number of projections. At first, the polychromatic spectra of X-ray beam and scatter can be modeled by a non-linear direct modeling in the statistical methods for the purpose of the metal artifacts reduction. However, the reconstruction by statistical methods is too much time consuming. Consequently, we proposed an iterative algorithm with a linear direct modeling based on data correction (beam-hardening and scatter). We introduced a new beam-hardening correction without knowledge of the spectra of X-ray source and the linear attenuation coefficients of the materials and a new scatter estimation method based on the measurements as well. Later, we continued to study the iterative approaches of dose reduction since the over-exposition or unnecessary exposition of irradiation during a CT scan has been increasing the patient's risk of radio-induced cancer. In practice, it may be useful that one can reconstruct an object larger than the field of view of scanner. We proposed an iterative algorithm on super-short-scans on multiple scans in this case, which contain a minimal set of the projections for an optimal dose. Furthermore, we introduced a new scanning mode of variant angular sampling to reduce the number of projections on a single scan. This was adapted to the properties and predefined interesting regions of the scanned object. It needed fewer projections than the standard scanning mode of uniform angular sampling to reconstruct the objet. All of our approaches for MAR and dose reduction have been evaluated on real data. Thanks to our MAR methods, the quality of reconstructed images was improved noticeably. Besides, it did not introduce some new artifacts compared to the MAR method of state of art NMAR [Meyer et al 2010]. We could reduce obviously the number of projections with the proposed new scanning mode and schema of super-short-scans on multiple scans in particular case.

Magister Scientiae (Medical Bioscience) - MSc(MBS) / This study investigated the effects of TKIs on the growth and proliferation of MCF-7 breast carcinoma cells in culture. MCF-7 cells were exposed to different concentrations of TKIs alone and in combination with each other. Inhibition of cell growth by TKIs used individually occurred in a dose- and time-dependent manner. When EGFR Inhibitor I, EGFR Inhibitor II/BIBX1382 and the multi-specific EGFR/ErbB-2/ErB-4 Inhibitor were used in combination with each other at equimolar log dose concentrations, the combined effects on cell growth was significantly different to inhibitors used individually as reflected in a decreased EC50 (IC50) during combination treatments. Generally, for the combinations with DOX, CPL and the TKIs, synergistic as well as antagonistic effects were observed at isoeffective concentrations with resultant decreases in dose reduction indices (DRIs) implying greater efficacies with the respective combinations. In this study, conventional PCR was used to detect and illustrate the presence of the EGFR gene in the samples, while RT-qPCR was used to determine the mRNA expression levels of this gene in MCF-7 breast carcinoma cells