We describe evaluations of the SRW-OSEM algorithm using clinical patient data. SRW-OSEM is an iterative reconstruction method which incorporates scatter and randoms corrections within the weighting component of the system matrix analogous to the attenuation weighted reconstruction algorithm. Our previous results obtained from small animal phantom data showed that SRW-OSEM can accelerate the reconstruction task and reduce the storage cost as well as improving the image quality. In this work, further evaluations were conducted using clinical patient data whose scatter fraction is much higher than the phantom data previously used. As a result, the trues fraction was ∼30%-50% for the patient data as compared to \textasciitilde 80% for the small animal phantom data. Convergence rate in contrast recovery and image profiles were compared between the SRWOSEM and OP-OSEM. Higher improvement in convergence rate with respect to OP-OSEM was observed from SRW-OSEM for the patient data as compared to the improvement observed previously from the small animal phantom data. As expected, the higher the background contamination (e.g. scatter and randoms fractions) the higher the improvement in convergence rate achieved by SRW-OSEM with respect to OP-OSEM. In particular, 3-4 times faster convergence rate with respect to OPOSEM was achieved by SRW-OSEM in this case; e.g. image reconstructed with 3 iterations of SRW-OSEM contains similar contrast as compared to that reconstructed with 12 iterations of OP-OSEM. Furthermore, lower noise was observed from the SRW-OSEM image as compared to the OP-OSEM image due to the lower number of iterations used in the reconstruction when the noise in the trues fraction estimate was low.
|Name||2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings|
|Conference||2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017|
|Period||21/10/2017 → 28/10/2017|