4D RECONSTRUCTION OF CARDIAC IMAGES USING TEMPORAL FOURIER BASIS FUNCTIONS

In cardiac imaging the data acquisition is often gated according to the ECG signal at the expense of signal to noise ratio in order to deal with cardiac motion. In this work, we propose a spatio-temporal reconstruction procedure by using a Fourier harmonic representation model for the temporal image activities. To further combat the increased imaging noise, we also include a spatial smoothing prior into the reconstruction process. We then reconstruct the different harmonics in the representation model by using both a penalized least-squares approach and a maximum a posteriori approach. In our experiments, the proposed approach was demonstrated using simulated cardiac SPECT perfusion imaging based on the NURBS-based cardiac-torso (NCAT) phantom.