Viewpoint Selection for Angiographic Volume

In this paper, we present a novel viewpoint selection framework for angiographic volume data. We propose several view descriptors based on typical concerns of clinicians for the view evaluation. Compared with conventional approaches, our method can deliver a more representative global optimal view by sampling at a much higher rate in the view space. Instead of performing analysis on sample views individually, we construct a solution space to estimate the quality of the views. Descriptor values are propagated to the solution space where an efficient searching process can be performed. The best viewpoint can be found by analyzing the accumulated descriptor values in the solution space based on different visualization goals.