Compton cameras localize γ-ray sources in 3D space by observing evidence of Compton scattering with detectors sensitive to ionizing radiation. This thesis proposes a software system for operating a novel Compton camera device comprised of Timepix3 detectors and Katherine readouts. To communicate with readouts using UDP-based protocol, a dedicated hardware library was developed. The presented software can successfully control the acquisition of multiple Timepix3 detectors and simultaneously process their measurements in a real-time setting. To recognize instances of Compton scattering among observed interactions, a chain of algorithms is applied with explicit consideration for a possibly high volume of measured information. Unlike alternate approaches, the presented work uses a recently published charge drift time model to improve its spatial resolution. In order to achieve localization of γ-ray sources, the software performs conical back projection into a discretized cuboid volume. Results of randomized evaluation with simulated data indicate that the presented implementation is correct and constitutes a viable method of γ-ray source localization in 3D space. Experimental verification with a prototype model is in progress.

<p>This licentiate thesis concerns the development and characterisation of X-ray imaging detector systems. “Colour” X-ray imaging opens up new perspectives within the fields of medical X-ray diagnosis and also in industrial X-ray quality control. The difference in absorption for different “colours” can be used to discern materials in the object. For instance, this information might be used to identify diseases such as brittle-bone disease. The “colour” of the X-rays can be identified if the detector system can process each X-ray photon individually. Such a detector system is called a “single photon processing” system or, less precise, a “photon counting system”.</p><p>With modern technology it is possible to construct photon counting detector systems that can resolve details to a level of approximately 50 µm. However with such small pixels a problem will occur. In a semiconductor detector each absorbed X-ray photon creates a cloud of charge which contributes to the picture achieved. For high photon energies the size of the charge cloud is comparable to 50 µm and might be distributed between several pixels in the picture. Charge sharing is a key problem since, not only is the resolution degenerated, but it also destroys the “colour” information in the picture.</p><p>The problem involving charge sharing which limits “colour” X-ray imaging is discussed in this thesis. Image quality, detector effectiveness and “colour correctness” are studied on pixellated detectors from the MEDIPIX collaboration. Characterisation measurements and simulations are compared to be able to understand the physical processes that take place in the detector. Simulations can show pointers for the future development of photon counting X-ray systems. Charge sharing can be suppressed by introducing 3D-detector structures or by developing readout systems which can correct the crosstalk between pixels.</p>

La tomodensitométrie par rayons-X (CT) est une modalité d’imagerie produisant une carte tridimensionnelle du coefficient d’atténuation des rayons-X d’un objet. En radiothérapie, le CT fournit de l’information anatomique et quantitative sur le patient afin de permettre la planification du traitement et le calcul de la dose de radiation à livrer. Le CT a plusieurs problèmes, notamment (1) une limitation au niveau de l’exactitude des paramètres physiques quantitatifs extraits du patient, et (2) une sensibilité aux biais causés par des artéfacts de durcissement du faisceau. Enfin, (3) dans le cas où le CT est fait en présence d’un agent de contraste pour améliorer la planification du traitement, il est nécessaire d’effectuer un deuxième CT sans agent de contraste à des fins de calcul de dose, ce qui augmente la dose au patient. Ces trois problèmes limitent l’efficacité du CT pour certaines modalités de traitement qui sont plus sensibles aux incertitudes comme la protonthérapie. Le CT spectral regroupe un ensemble de méthodes pour produire plusieurs cartes d’atténuation des rayons-X moyennées sur différentes plages énergétiques. L’information supplémentaire, pondérée en énergie qui est obtenue permet une meilleure caractérisation des matériaux analysés. Le potentiel de l’une de ces modalités spectrales, le CT bi-énergie (DECT), est déjà bien démontré en radiothérapie, alors qu’une approche en plein essor, le CT spectral à comptage de photons (SPCCT), promet davantage d’information spectrale à l’aide de détecteurs discriminateurs en énergie. Par contre, le SPCCT souffre d’un bruit plus important et d’un conditionnement réduit. Cette thèse investigue la question suivante : y a-t-il un bénéfice à utiliser plus d’information résolue en énergie, mais de qualité réduite pour la radiothérapie ? La question est étudiée dans le contexte des trois problèmes ci-haut. Tout d’abord, un estimateur maximum a posteriori (MAP) est introduit au niveau de la caractérisation des tissus post-reconstruction afin de débruiter les données du CT spectral. L’approche est validée expérimentalement sur un DECT. Le niveau de bruit du pouvoir d’arrêt des protons diminue en moyenne d’un facteur 3.2 à l’aide de l’estimateur MAP. Celui-ci permet également de conserver généralement le caractère quantitatif des paramètres physiques estimés, le pouvoir d’arrêt variant en moyenne de 0.9% par rapport à l’approche conventionnelle. Ensuite, l’estimateur MAP est adapté au contexte de l’imagerie avec agent de contraste. Les résultats numériques démontrent un bénéfice clair à utiliser le SPCCT pour l’imagerie virtuellement sans contraste par rapport au DECT, avec une réduction de l’erreur RMS sur le pouvoir d’arrêt des protons de 2.7 à 1.4%. Troisièmement, les outils développés ci-haut sont validés expérimentalement sur un micro-SPCCT de la compagnie MARS Bioimaging, dont le détecteur à comptage de photons est le Medipix 3, qui est utilisé pour le suivi de particules au CERN. De légers bénéfices au niveau de l’estimation des propriétés physiques à l’aide du SPCCT par rapport au DECT sont obtenus pour des matériaux substituts à des tissus humains. Finalement, une nouvelle paramétrisation du coefficient d’atténuation pour l’imagerie pré-reconstruction est proposée, dans le but ultime de corriger les artéfacts de durcissement du faisceau. La paramétrisation proposée élimine les biais au niveau de l’exactitude de la caractérisation des tissus humains par rapport aux paramétrisations existantes. Cependant, aucun avantage n’a été obtenu à l’aide du SPCCT par rapport au DECT, ce qui suggère qu’il est nécessaire d’incorporer l’estimation MAP dans l’imagerie pré-reconstruction via une approche de reconstruction itérative. / X-ray computed tomography (CT) is an imaging modality that produces a tridimensional map of the attenuation of X-rays by the scanned object. In radiation therapy, CT provides anatomical and quantitative information on the patient that is required for treatment planning. However, CT has some issues, notably (1) a limited accuracy in the estimation of quantitative physical parameters of the patient, and (2) a sensitivity to biases caused by beam hardening artifacts. Finally, (3) in the case where contrast-enhanced CT is performed to help treatment planning, a second scan with no contrast agent is required for dose calculation purposes, which increases the overall dose to the patient. Those 3 problems limit the efficiency of CT for some treatment modalities more sensitive to uncertainties, such as proton therapy. Spectral CT regroups a set of methods that allows the production of multiple X-ray attenuation maps evaluated over various energy windows. The additional energy-weighted information that is obtained allows better material characterization. The potential of one spectral CT modality, dual-energy CT (DECT), is already well demonstrated for radiation therapy, while an upcoming method, spectral photon counting CT (SPCCT), promises more spectral information with the help of energy discriminating detectors. Unfortunately, SPCCT suffers from increased noise and poor conditioning. This thesis thus investigates the following question: is there a benefit to using more, but lower quality energy-resolved information for radiotherapy? The question is studied in the context of the three problems discussed earlier. First, a maximum a posteriori (MAP) estimator is introduced for post-reconstruction tissue characterization for denoising purposes in spectral CT. The estimator is validated experimentally using a commercial DECT. The noise level on the proton stopping power is reduced, on average, by a factor of 3.2 with the MAP estimator. The estimator also generally con- serves the quantitative accuracy of estimated physical parameters. For instance, the stopping power varies on average by 0.9% with respect to the conventional approach. Then, the MAP estimation framework is adapted to the context of contrast-enhanced imaging. Numerical results show clear benefits when using SPCCT for virtual non-contrast imaging compared to DECT, with a reduction of the RMS error on the proton stopping power from 2.7 to 1.4%. Third, the developed tools are validated experimentally on a micro-SPCCT from MARS Bioimaging, which uses the Medipix 3 chip as a photon counting detector. Small benefits in the accuracy of physical parameters of tissue substitutes materials are obtained. Finally, a new parametrization of the attenuation coefficient for pre-reconstruction imaging is pro- posed, whose ultimate aim is to correct beam hardening artifacts. In a simulation study, the proposed parametrization eliminates all biases in the estimated physical parameters of human tissues, which is an improvement upon existing parametrizations. However, no ad- vantage has been obtained with SPCCT compared to DECT, which suggests the need to incorporate MAP estimation in the pre-reconstruction framework using an iterative reconstruction approach.

This thesis concerns the development and characterisation of X-ray imaging systems based on single photon processing. “Colour” X-ray imaging opens up new perspectives within the fields of medical X-ray diagnosis and also in industrial X-ray quality control. The difference in absorption for different “colours” can be used to discern materials in the object. For instance, this information might be used to identify diseases such as brittle-bone disease. The “colour” of the X-rays can be identified if the detector system can process each X-ray photon individually. Such a detector system is called a “single photon processing” system or, less precise, a “photon counting system”. With modern technology it is possible to construct photon counting detector systems that can resolve details to a level of approximately 50 µm. However with such small pixels a problem will occur. In a semiconductor detector each absorbed X-ray photon creates a cloud of charge which contributes to the image. For high photon energies the size of the charge cloud is comparable to 50 µm and might be distributed between several pixels in the image. Charge sharing is a key problem since, not only is the resolution degenerated, but it also destroys the “colour” information in the image. This thesis presents characterisation and simulations to provide a detailed understanding of the physical processes concerning charge sharing in detectors from the MEDIPIX collaboration. Charge summing schemes utilising pixel to pixel communications are proposed. Charge sharing can also be suppressed by introducing 3D-detector structures. In the next generation of the MEDIPIX system, Medipix3, charge summing will be implemented. This system, equipped with a 3D-silicon detector, or a thin planar high-Z detector of good quality, has the potential to become a commercial product for medical imaging. This would be beneficial to the public health within the entire European Union. / Denna avhandling berör utveckling och karaktärisering av fotonräknande röntgensystem. ”Färgröntgen” öppnar nya perspektiv för medicinsk röntgendiagnostik och även för materialröntgen inom industrin. Skillnaden i absorption av olika ”färger” kan användas för att särskilja olika material i ett objekt. Färginformationen kan till exempel användas i sjukvården för att identifiera benskörhet. Färgen på röntgenfotonen kan identifieras om detektorsystemet kan detektera varje foton individuellt. Sådana detektorsystem kallas ”fotonräknande” system. Med modern teknik är det möjligt att konstruera fotonräknande detektorsystem som kan urskilja detaljer ner till en upplösning på circa 50 µm. Med så små pixlar kommer ett problem att uppstå. I en halvledardetektor ger varje absorberad foton upphov till ett laddningsmoln som bidrar till den erhållna bilden. För höga fotonenergier är storleken på laddningsmolnet jämförbar med 50 µm och molnet kan därför fördelas över flera pixlar i bilden. Laddningsdelning är ett centralt problem delvis på grund av att bildens upplösning försämras, men framför allt för att färginformationen i bilden förstörs. Denna avhandling presenterar karaktärisering och simulering för att ge en mer detaljerad förståelse för fysikaliska processer som bidrar till laddningsdelning i detektorer från MEDIPIX-projekter. Designstrategier för summering av laddning genom kommunikation från pixel till pixel föreslås. Laddningsdelning kan också begränsas genom att introducera detektorkonstruktioner i 3D-struktur. I nästa generation av MEDIPIX-systemet, Medipix3, kommer summering av laddning att vara implementerat. Detta system, utrustat med en 3D-detektor i kisel, eller en tunn plan detektor av högabsorberande material med god kvalitet, har potentialen att kunna kommersialiseras för medicinska röntgensystem. Detta skulle bidra till bättre folkhälsa inom hela Europeiska Unionen.

This licentiate thesis concerns the development and characterisation of X-ray imaging detector systems. “Colour” X-ray imaging opens up new perspectives within the fields of medical X-ray diagnosis and also in industrial X-ray quality control. The difference in absorption for different “colours” can be used to discern materials in the object. For instance, this information might be used to identify diseases such as brittle-bone disease. The “colour” of the X-rays can be identified if the detector system can process each X-ray photon individually. Such a detector system is called a “single photon processing” system or, less precise, a “photon counting system”. With modern technology it is possible to construct photon counting detector systems that can resolve details to a level of approximately 50 µm. However with such small pixels a problem will occur. In a semiconductor detector each absorbed X-ray photon creates a cloud of charge which contributes to the picture achieved. For high photon energies the size of the charge cloud is comparable to 50 µm and might be distributed between several pixels in the picture. Charge sharing is a key problem since, not only is the resolution degenerated, but it also destroys the “colour” information in the picture. The problem involving charge sharing which limits “colour” X-ray imaging is discussed in this thesis. Image quality, detector effectiveness and “colour correctness” are studied on pixellated detectors from the MEDIPIX collaboration. Characterisation measurements and simulations are compared to be able to understand the physical processes that take place in the detector. Simulations can show pointers for the future development of photon counting X-ray systems. Charge sharing can be suppressed by introducing 3D-detector structures or by developing readout systems which can correct the crosstalk between pixels.