Accurate image reconstruction for DOI-PET systems and its implications for the development of economic, compact PET (ezPET) systems

We study the use of computationally efficient sinogram restoration (SR) approach for reconstruction of PET data acquired by systems with depth-of-interaction (DOI-PET) capability. Our preliminary results show that the proposed approach can yield images of excellent resolution uniformity for a hypothetical compact system with a field-of-view (FOV) as large as 98% of the detector ring size. In comparison with images generated by the conventional rebinning approach, the resolution uniformity across the FOV in the image produced by incorporating SR is improved by a factor of 6, and the spatial resolution at the edge of the FOV is improved by a factor of 2. Moreover, the SR approach produces better intensity recovery and peak positioning. Integration of the use of DOI detectors and SR reconstruction can thus provide a new way for developing economic, compact PET (ezPET) systems. We demonstrate that this ezPET design can produce images of quality comparable with those obtained by a conventional system that employs a detector ring ~50% larger than the compact system. The much reduced detector ring size of the ezPET system can provide greatly reduced production cost, improved image resolution and resolution uniformity, and increased system sensitivity