PET reconstruction algorithms have long relied on sinogram rebinning. However, as detectors grow smaller in a recent wave of cutting-edge scanners, individual sensors no longer accrue hundreds of photons. Instead, most detect a single photon or none at all, effectively turning sinogram data into point-cloud measurements. The highly heterogeneous sensitivity of these scanners is another issue. We approach sinogram rebinning in the face of these challenges with a density-estimation framework that promotes knot sparsity in an underlying spline basis.
Title
PET REBINNING WITH REGULARIZED DENSITY SPLINES
Published in
2023 Ieee 20Th International Symposium On Biomedical Imaging, Isbi
Conference
20th IEEE International Symposium on Biomedical Imaging (ISBI), APR 18-21, 2023, Cartagena, COLOMBIA
Date
2023-01-01
Publisher
IEEE, New York
ISSN
1945-7928
ISBN
978-1-6654-7358-3
Grant
Swiss National Science Foundation under the Sinergia grant: CRSII5 198569
Lausanne University Hospital (CHUV)
University of Lausanne (UNIL)
Ecole polytechnique federale de Lausanne (EPFL)
University of Geneva (UNIGE)
Geneva University Hospitals (HUG)
Swiss National Science Foundation (SNF): CRSII5_198569
Record creation date
2024-02-16