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Published in:
2015 | OriginalPaper | Chapter
Robust Identification of Contrasted Frames in Fluoroscopic Images
Authors : Matthias Hoffmann, Simone Müller, Klaus Kurzidim, Norbert Strobel, Joachim Hornegger
Published in: Bildverarbeitung für die Medizin 2015
Publisher: Springer Berlin Heidelberg
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For automatic registration of 3-D models of the left atrium to fluoroscopic images, a reliable classification of images containing contrast agent is necessary. Inspired by previous approaches on contrast agent detection, we propose a learning-based framework which is able to classify contrasted frames more robustly than previous methods, Furthermore, we performed a quantitative evaluation on a clinical data set consisting of 34 angiographies. Our learning-based approach reached a classification rate of 79.5%. The beginning of a contrast injection was detected correctly in 79.4%.