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In this paper we address the problem of automatic selection of important vessel-depicting key frames within 2D angiography videos. Two different methods of frame selection are described, one based on Frangi filter, and the other based on detecting parallel curves formed from edges in angiography images. Results are shown by comparison to physician annotation of such key frames on 2D coronary angiograms.
During a 2D echo exam, the transducer position is varied to elicit important information about the heart function and its anatomy. Knowledge of the transducer viewpoint is important in automatic cardiac echo interpretation to understand the regions being depicted as well as in the quantification of their attributes. In this paper, we address the problem of inferring the transducer viewpoint from the...
In this paper we present a method of simultaneous registration of an entire sequence of frames of an echocardiographic sequence. In our approach, each echo frame is modeled using a probability density function, and registration problem between all pairs of echo frames is formulated as the problem of matching probability densities. An information-theoretic criterion called the Jensen-Renyi divergence...
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