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Fully Automatic Segmentation of Papillary Muscles in 3D LGE-MRI.

, , , , , and . Bildverarbeitung für die Medizin, page 11-16. Springer, (2017)

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LV function validation of computer-assisted interventional system for cardiac resyncronisation therapy., , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (6): 777-786 (2018)Training Deep Networks on Domain Randomized Synthetic X-ray Data for Cardiac Interventions., , , , , and . MIDL, volume 102 of Proceedings of Machine Learning Research, page 468-482. PMLR, (2019)Left ventricle segmentation in LGE-MRI using multiclass learning., , , , and . Medical Imaging: Image Processing, volume 10949 of SPIE Proceedings, page 1094929. SPIE, (2019)Myocardial Scar Segmentation in LGE-MRI using Fractal Analysis and Random Forest Classification., , , , , and . ICPR, page 3168-3173. IEEE Computer Society, (2018)Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair., , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (8): 1221-1231 (2018)Image Data Analysis for Quantifying Scar Transmurality in MRI phantoms for Cardiac Resynchronisation Therapy., , , , , , , , and . EMBC, page 1111-1114. IEEE, (2018)3D/2D model-to-image registration by imitation learning for cardiac procedures., , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (8): 1141-1149 (2018)Mechanical Activation Computation from Fluoroscopy for Guided Cardiac Resynchronization Therapy., , , , and . EMBC, page 592-595. IEEE, (2018)Workflow Phase Detection in Fluoroscopic Images Using Convolutional Neural Networks., , , , , , and . Bildverarbeitung für die Medizin, page 191-196. Springer Vieweg, (2019)Fully Automatic Segmentation of Anatomy and Scar from LGE-MRI (Vollautomatische Segmentierung von Anatomie und Narben in LGE-MRI). University of Erlangen-Nuremberg, Germany, (2018)base-search.net (ftuniverlangen:oai:ub.uni-erlangen.de-opus:10250).