The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used.

The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used.

Η παρούσα διδακτορική διατριβή αποτελεί μια μελέτη σύγκρισης και βελτιστοποίησης διάφορων αλγορίθμων ανακατασκευής δεδομένων, τα οποία προέρχονται από ένα πρότυπο σύστημα ΡΕΤ ικανό για απεικονίσεις μικρών ζώων. Η σύγκριση αφορά υπάρχοντες αλγορίθμους ανακατασκευής ενώ παρουσιάζεται και ένας νέος επαναληπτικός αλγόριθμος o ISWLS. Το δεύτερο μέρος της παρούσας διδακτορικής διατριβής ασχολείται με ένα άλλο σημαντικό στάδιο της επεξεργασίας ιατρικών δεδομένων την τμηματοποίηση της ιατρικής εικόνας. Παρουσιάζονται διάφορες τεχνικές παραμετρικών ελαστικών μοντέλων. Συγκεκριμένα παρουσιάζονται το κλασσικό μοντέλο φιδιού (snake), το μοντέλο gradient vector flow (gvf-snake) και τα t-snakes (topology-adaptive snakes). Επίσης παρουσιάζεται η μέθοδος self-affine mapping σαν μια εναλλακτική των παραπάνω παραμετρικών ελαστικών μοντέλων και εισάγεται ένα νέο κριτήριο σύγκλισής της. Όλες οι τεχνικές εφαρμόζονται σε οφθαλμικές εικόνες με σκοπό την τμηματοποίηση του οπτικού δίσκου / Small animal imaging is the conjunctive ring between experimental research and clinical implementation. Positron Emission Tomography (PET) has proven a valuable tool for in vivo small animal functional imaging. Image reconstruction in PET uses the collected projection data of the object/patient under examination. The purpose of this study is to assess the performance of iterative reconstruction methods, using phantom data from a prototype small-animal PET system. The algorithms being compared are the simultaneous versions of ART (SART), EM-ML, ISRA and WLS and a new iterative algorithm being introduced under the short name ISWLS. In the second part of this thesis elastic or deformable models are studied. Various methods of parametric elastic models are presented, namely the classical snake, the gradient vector field snake (gvf-snake) and the topogy-adaptive snake (t-snake). Also presented the method of self-affine mapping system as an alternative of elastic models. Further a new comparison criterion for the self affine mapping system method is introduced. All methods are applied to retinal images with the purpose of segmenting the optical disk. Moreover the aforementioned methods are compared in terms of segmentation accuracy.

The images in positron emission tomography (PET) represent three dimensional dynamic distributions of biologically interesting molecules labelled with positron emitting radionuclides (radiotracers). Spatial localisation of the radio-tracers is achieved by detecting in coincidence two collinear photons which are emitted when the positron annihilates with an ordinary electron. In order to obtain quantitatively accurate images in PET, it is necessary to correct for the effects of photon attenuation within the subject being imaged. These corrections can be obtained using singles-mode photon transmission scanning. Although suitable for small animal PET, these scans are subject to high amounts of contamination from scattered photons. Currently, no accurate correction exists to account for scatter in these data. The primary purpose of this work was to implement and validate an analytical scatter correction for PET transmission scanning. In order to isolate the effects of scatter, we developed a simulation tool which was validated using experimental transmission data. We then presented an analytical scatter correction for singles-mode transmission data in PET. We compared our scatter correction data with the previously validated simulation data for uniform and non-uniform phantoms and for two different transmission source radionuclides. Our scatter calculation correctly predicted the contribution from scattered photons to the simulated data for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for simulated and experimental PET transmission data for uniform and non-uniform phantoms. We also tested our reconstruction and scatter correction procedure using transmission data for several animal studies (mice, rats and primates). For all studies considered, we found that the average reconstructed linear attenuation coefficients for water or soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2 GHz processor, the scatter correction required between 6 to 27 minutes of CPU time (without any code optimisation) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed attenuation coefficients were between 18 to 45% depending on the phantom size and transmission source used. / Science, Faculty of / Physics and Astronomy, Department of / Graduate

Positron emission tomography (PET) is a well-established functional imaging method used in nuclear medicine. It allows for retrieving information about biochemical and physiological processes in vivo. The currently possible spatial resolution of PET is about 5 mm for brain acquisitions and about 8 mm for whole-body acquisitions, while recent improvements in image reconstruction point to a resolution of 2 mm in the near future. Typical acquisition times range from minutes to hours due to the low signal-to-noise ratio of the measuring principle, as well as due to the monitoring of the metabolism of the patient over a certain time. Therefore, patient motion increasingly limits the possible spatial resolution of PET. In addition, patient immobilisations are only of limited benefit in this context. Thus, patient motion leads to a relevant resolution degradation and incorrect quantification of metabolic parameters. The present work describes the utilisation of a novel motion compensation method for clinical brain PET acquisitions. By using an external motion tracking system, information about the head motion of a patient is continuously acquired during a PET acquisition. Based on the motion information, a newly developed event-based motion compensation algorithm performs spatial transformations of all registered coincidence events, thus utilising the raw data of a PET system - the so-called `list-mode´ data. For routine acquisition of this raw data, methods have been developed which allow for the first time to acquire list-mode data from an ECAT Exact HR+ PET scanner within an acceptable time frame. Furthermore, methods for acquiring the patient motion in clinical routine and methods for an automatic analysis of the registered motion have been developed. For the clinical integration of the aforementioned motion compensation approach, the development of additional methods (e.g. graphical user interfaces) was also part of this work. After development, optimisation and integration of the event-based motion compensation in clinical use, analyses with example data sets have been performed. Noticeable changes could be demonstrated by analysis of the qualitative and quantitative effects after the motion compensation. From a qualitative point of view, image artefacts have been eliminated, while quantitatively, the results of a tracer kinetics analysis of a FDOPA acquisition showed relevant changes in the R0k3 rates of an irreversible reference tissue two compartment model. Thus, it could be shown that an integration of a motion compensation method which is based on the utilisation of the raw data of a PET scanner, as well as the use of an external motion tracking system, is not only reasonable and possible for clinical use, but also shows relevant qualitative and quantitative improvement in PET imaging. / Die Positronen-Emissions-Tomographie (PET) ist ein in der Nuklearmedizin etabliertes funktionelles Schnittbildverfahren, das es erlaubt Informationen über biochemische und physiologische Prozesse in vivo zu erhalten. Die derzeit erreichbare räumliche Auflösung des Verfahrens beträgt etwa 5 mm für Hirnaufnahmen und etwa 8 mm für Ganzkörperaufnahmen, wobei erste verbesserte Bildrekonstruktionsverfahren eine Machbarkeit von 2 mm Auflösung in Zukunft möglich erscheinen lassen. Durch das geringe Signal/Rausch-Verhältnis des Messverfahrens, aber auch durch die Tatsache, dass der Stoffwechsel des Patienten über einen längeren Zeitraum betrachtet wird, betragen typische PET-Aufnahmezeiten mehrere Minuten bis Stunden. Dies hat zur Folge, dass Patientenbewegungen zunehmend die erreichbare räumliche Auflösung dieses Schnittbildverfahrens limitieren. Eine Immobilisierung des Patienten zur Reduzierung dieser Effekte ist hierbei nur bedingt hilfreich. Es kommt daher zu einer relevanten Auflösungsverschlechterung sowie zu einer Verfälschung der quantifizierten Stoffwechselparameter. Die vorliegende Arbeit beschreibt die Nutzbarmachung eines neuartigen Bewegungskorrekturverfahrens für klinische PET-Hirnaufnahmen. Mittels eines externen Bewegungsverfolgungssystems wird während einer PET-Untersuchung kontinuierlich die Kopfbewegung des Patienten registriert. Anhand dieser Bewegungsdaten führt ein neu entwickelter event-basierter Bewegungskorrekturalgorithmus eine räumliche Korrektur aller registrierten Koinzidenzereignisse aus und nutzt somit die als "List-Mode" bekannten Rohdaten eines PET Systems. Für die Akquisition dieser Daten wurden eigens Methoden entwickelt, die es erstmals erlauben, diese Rohdaten von einem ECAT Exact HR+ PET Scanner innerhalb eines akzeptablen Zeitraumes zu erhalten. Des Weiteren wurden Methoden für die klinische Akquisition der Bewegungsdaten sowie für die automatische Auswertung dieser Daten entwickelt. Ebenfalls Teil der Arbeit waren die Entwicklung von Methoden zur Integration in die klinische Routine (z.B. graphische Nutzeroberflächen). Nach der Entwicklung, Optimierung und Integration der event-basierten Bewegungskorrektur für die klinische Nutzung wurden Analysen anhand von Beispieldatensätzen vorgenommen. Es zeigten sich bei der Auswertung sowohl der qualitativen als auch der quantitativen Effekte deutliche Änderungen. In qualitativer Hinsicht wurden Bildartefakte eliminiert; bei der quantitativen Auswertung einer FDOPA Messung zeigte sich eine revelante Änderung der R0k3 Einstromraten eines irreversiblen Zweikompartment-Modells mit Referenzgewebe. Es konnte somit gezeigt werden, dass eine Integration einer Bewegungskorrektur unter Zuhilfenahme der Rohdaten eines PET Systems sowie unter Nutzung eines externen Verfolgungssystems nicht nur sinnvoll und in der klinischen Routine machbar ist, sondern auch zu maßgeblichen qualitativen und quantitativen Verbesserungen in der PET-Bildgebung beitragen kann.