A method for determining a
convolution kernel for an iterative
statistical algorithm based on a continuous-to-
continuous data model. The method is used for image reconstruction from
radiation measurements obtained in emission
tomography, specifically in a Time-of-Flight
Positron Emission
Tomography (TOF PET)
scanner. The presented method is a non-
list-mode solution that reduces the computational complexity of the
reconstruction problem, improves the resolution of reconstructed images, reduces the
radiation dose absorbed by patients during TOF PET examinations, and / or shortens the measurement
acquisition time without significantly compromising the quality of the diagnostic images. Notably, the quality of the functional images remains at the same level. These improvements are achieved by designing the
convolution kernel to account for the statistical properties of the measurement signals registered during the TOF
PET scanner's acquisition process.