Optimization, evaluation, and comparison of standard algorithms for image reconstruction with the VIP-PET

A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project []. The simulation results show a great potential of the VIP to produce high-resolution...

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Detalhes bibliográficos
Autores: Mikhaylova, Ekaterina|||0000-0002-6145-495X, Kolstein, Machiel|||0000-0002-5482-6743, De Lorenzo, Gianluca|||0000-0003-1795-0988, Chmeissani, Mokhtar|||0000-0002-2287-4791
Formato: artículo
Fecha de publicación:2014
País:España
Recursos:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:185066
Acesso em linha:https://ddd.uab.cat/record/185066
https://dx.doi.org/urn:doi:10.1088/1748-0221/9/07/C07004
Access Level:acceso abierto
Palavra-chave:Medical-image reconstruction methods and algorithms
Computer-aided software
Gamma camera
SPECT
PET PET/CT
Coronary CT angiography (CTA)
Descrição
Resumo:A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project []. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head []. With unprecedented high channel density (450 channels/cm 3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [] simulation including the expected CdTe and electronic specifics.