SPECT reconstruction with non-uniform attenuation from highly under-sampled projection data

Single photon emission computed tomography (SPECT) is an important nuclear medicine imaging technique and has been using in clinical diagnoses. The SPECT image can reflect not only organizational structure but also functional activities of human body, therefore diseases can be found much earlier. In SPECT, the reconstruction is based on the measurement of gamma photons emitted by the radiotracer. The number of gamma photons detected is proportional to the dose of radiopharmaceutical, but the dose is limited because of patient safety. There is an upper limit in the number of gamma photons that can be detected per unit time, so it takes a long time to acquire SPECT projection data. Sometimes we just can obtain highly under-sampled projection data because of the limit of the scanning time or imaging hardware. How to reconstruct an image using highly under-sampled projection data is an interesting problem. One method is to minimize the total variation (TV) of the reconstructed image during the iterative reconstruction. In this work, we developed an OSEM-TV SPECT reconstruction algorithm, which could reconstruct the image from highly under-sampled projection data with non-uniform attenuation. Simulation results demonstrate that the OSEM-TV algorithm performs well in SPECT reconstruction with non-uniform attenuation.