Reconstruction of positron emission tomography images using adaptive sliced remeshing strategy

COLMEIRO, RAMIRO R.; VERRASTRO, CLAUDIO; MINSKY, DANIEL; GROSGES, THOMAS

Journal of Medical Imaging

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Lugar: Bellingham; Año: 2021 vol. 8

Purpose: The reconstruction of positron emission tomography images is a computationally inten-sive task which benefits from the use of increasingly complex physical models. Aiming to reducethe computational burden by means of a reduced system matrix, we present a list mode reconstruc-tion approach based on maximum likelihood-expectation maximization and a sliced mesh support.Approach: The reconstruction strategy uses a fully 3D projection along series of 2D meshesarranged in the axial plane of the scanner. These series of meshes describe the continuous volu-metric activity using a piece-wise linear function interpolated from the mesh elements. The meshsupport is automatically adapted to the underlying structure of the activity by means of a remesh-ing process. This process finds a high-quality compact mesh representation constrained to acontrolled interpolation error.Results: The method is tested using a Monte Carlo simulation of a Hoffman brain phantom and aNational Electrical Manufacturers Association image quality phantom acquisition, using differ-ent sets of statistics. The reconstructions are compared against a voxelized reconstruction underdifferent conditions, achieving similar or superior results. The number of parameters needed toreconstruct the image in voxel and mesh support is also compared, and the mesh reconstructionpermits to reduce the number of nodes used to represent a complex image.Conclusions: The proposed reconstruction strategy reduces the number of parameters needed todescribe the activity distribution by more than one order of magnitude for similar voxel size andwith similar accuracy than state-of-the-art methods.