Performance comparison of different motion correction algorithms used in cardiac SPECT imaging

We evaluate the performance and accuracy of different motion correction algorithms used in nuclear cardiac imaging. Three algorithms used in automated tracking techniques are the diverging square (DS); diverging circles (DC); and self-adaptive masking methods (SM). The observation of the tracking process over the images acquired (specifically for this study with introduced patient motion) in nuclear cardiac laboratory showed that the DC and SM algorithms perform better when compared with the DS algorithm. It was shown that the SM method gains a good tolerance of low signal to noise ratio (SNR) images and is also robust in the presence of abrupt motion