TY - CHAP A1 - Hoffmann, Matthias A1 - Müller, Simone A1 - Kurzidim, Klaus A1 - Strobel, Norbert A1 - Hornegger, Joachim T1 - Robust Identification of Contrasted Frames in Fluoroscopic Images T2 - Bildverarbeitung für die Medizin 2015 N2 - 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%. Y1 - 2015 SN - 978-3-662-46223-2 SN - 978-3-662-46224-9 U6 - https://doi.org/10.1007/978-3-662-46224-9_6 PB - Springer Vieweg CY - Berlin, Heidelberg ER -