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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)

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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)Multiple Device Segmentation for Fluoroscopic Imaging Using Multi-task Learning., , , , , , , and . CVII-STENT/LABELS@MICCAI, volume 11043 of Lecture Notes in Computer Science, page 19-27. Springer, (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)Cryo-Balloon Catheter Localization Based on a Support-Vector-Machine Approach., , , , and . IEEE Trans. Med. Imaging, 35 (8): 1892-1902 (2016)Fully automatic segmentation of left ventricular anatomy in 3-D LGE-MRI., , , , , and . Comp. Med. Imag. and Graph., (2017)Real-time motion-adjusted augmented fluoroscopy system for navigation during electrophysiology procedures., , , , , , , , and . Medical Imaging: Image-Guided Procedures, volume 8316 of SPIE Proceedings, page 831626. SPIE, (2012)Mechanical Activation Computation from Fluoroscopy for Guided Cardiac Resynchronization Therapy., , , , and . EMBC, page 592-595. IEEE, (2018)Random Forest Based Left Ventricle Segmentation in LGE-MRI., , , and . FIMH, volume 10263 of Lecture Notes in Computer Science, page 152-160. Springer, (2017)Workflow Phase Detection in Fluoroscopic Images Using Convolutional Neural Networks., , , , , , and . Bildverarbeitung für die Medizin, page 191-196. Springer Vieweg, (2019)