Abstract
Rotational coronary angiography allows for volumetric imaging but requires cardiac and respiratory motion management to achieve meaningful reconstructions. Novel respiratory motion compensation algorithms based on data consistency conditions are applied directly in projection domain and, therefore, overcome the need for uncompensated reconstructions. Earlier, we combined single-frame background subtraction and epipolar consistency conditions to compensate for respiratory motion. In this paper, we show that background subtraction also enables motion estimation via optimization of novel Fourier consistency conditions. The proposed method is evaluated in a numerical phantom study. Compared to the uncompensated case, we found a reduction in residual root-mean-square error of 89% when Fourier consistency conditions were used. The results are promising and encourage experiments on clinical data.
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