Lesion detectability and quantification in fluorine-18-fluorodeoxyglucose positron emission tomography oncological studies are highly affected by space variant blur. The performance of spatial resolution recovery during AWOSEM iterative reconstruction was assessed by including in the system matrix a simple model of point spread function fitted on experimentally acquired point source sinograms. The model described axial, tangential and radial blur; radial asymmetry was taken into account. The algorithm properties in terms of contrast recovery, image noise and object separability were evaluated on scanned sphere phantom studies both in 2-D and 3-D mode. Extensive comparisons of standard and resolution recovery algorithms, over wide parameter ranges with and without post-filtering are presented. Resolution recovery, by delaying noise breakup appearance and by increasing contrast, was able to improve overall accuracy, particularly for small objects and large blur. The recovery of axial blur resulted determinant in 3-D and even more in 2-D mode. The optimal choice of reconstruction parameters was shown to be highly object dependent, thus suggesting an algorithm tuning according to applications.Index Terms-Image reconstructiom, ordered subset expectation maximization (OSEM), positron emission tomography (PET), spatial resolution.

Fourier rebinning (FORE) is the most widely used rebinning algorithm to reorganize 3-D PET data into 2-D sinograms. In Fourier transform (FT) domain, data from oblique sinograms are assigned to transaxial ones at a proper axial displacement given by the frequency-distance relation. Approximation accuracy falls at low frequencies, where only low-copolar angles can be exploited by means of single slice rebinning (SSRB). Usually, an abrupt partition by a square region centered on DC is applied, which does not weight accuracy in the sinogram FT domain and copolar angle dependence, and can introduce artifacts due to the sharp transition. In this work we propose a simple index which maps the frequencydistance relation validity in the sinogram FT domain. Two new criteria were tested on this basis: 1) an abrupt transition based on validity map contours and 2) a gradual transition following the monotonical validity increase with frequency. In both criteria copolar angle dependence was introduced. Standard, abrupt, and gradual partitions were compared on different phantoms acquired with ECAT EXACT HR+ scanner, characterized by a large span = 9 (saved sinograms group 4 or 5 acquired sinograms, by averaging) and by a low maximum copolar angle (6 ). In this condition the methods provided similar tradeoffs of SNR optimization against blur and artifact appearance, thus confirming the validity of the frequency-distance relation at low copolar angles. A simulation study emulating an hypothetical scanner with span = 3 and larger acceptance copolar angle (25 5 ) conversely showed more clear improvements.

Statistical Shape Models (SSMs) are well-established tools for assessing the variability of 3D geometry and for broadening a limited set of shapes. They are widely used in medical imaging due to their ability to model complex geometries and their high efficiency as generative models. The principal step behind these techniques is a registration phase, which, in the case of complex geometries, can be a critical issue due to the correspondence problem, as it necessitates the development of correspondence mapping between shapes. The thoracic aorta, with its high level of morphological complexity, poses a multi-scale deformation problem due to the presence of several branch vessels with varying diameters. Moreover, branch vessels exhibit significant variability in shape, making the correspondence optimization even more challenging. Consequently, existing studies have focused on developing SSMs based only on the main body of the aorta, excluding the supra-aortic vessels from the analysis. In this work, we present a novel non-rigid registration algorithm based on optimizing a differentiable distance function through a modified gradient descent approach. This strategy enables the inclusion of custom, domain-specific constraints in the objective function, which act as landmarks during the registration phase. The algorithm’s registration performance was tested and compared to an alternative Statistical Shape modeling framework, and subsequently used for the development of a comprehensive SSM of the thoracic aorta, including the supra-aortic vessels. The developed SSM was further evaluated against the alternative framework in terms of generalisation, specificity, and compactness to assess its effectiveness.

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