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Patient Surface Model and Internal Anatomical Landmarks Embedding., , , , , и . Bildverarbeitung für die Medizin, стр. 43-48. Springer Vieweg, (2018)Automatic Detection of Ostia in the Left Atrium., , , и . Bildverarbeitung für die Medizin, стр. 224-229. Springer, (2016)Model-Based Motion Artifact Correction in Digital Subtraction Angiography Using Optical-Flow., , , , , , и . Bildverarbeitung für die Medizin, стр. 146-151. Springer Vieweg, (2019)Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment., , , , , , , и . ICAR, стр. 857-864. IEEE, (2021)Abstract: Simultaneous Estimation of X-ray Back-scatter and Forward-scatter using Multi-task Learning., , , , , , , , , и . Bildverarbeitung für die Medizin, стр. 262. Springer, (2021)Learning a multiscale patch-based representation for image denoising in X-RAY fluoroscopy., , , , , , и . ICIP, стр. 2330-2334. IEEE, (2016)A Data-Driven Model for Range Sensors., , , и . Int. J. Semantic Comput., 18 (2): 205-222 (июня 2024)Fully Truncated Cone-Beam Reconstruction on Pi Lines Using Prior CT., , , и . MICCAI, том 3749 из Lecture Notes in Computer Science, стр. 631-638. Springer, (2005)An analytical approach for the simulation of realistic low-dose fluoroscopic images., , , , , и . Int. J. Comput. Assist. Radiol. Surg., 14 (4): 601-610 (2019)A machine learning pipeline for internal anatomical landmark embedding based on a patient surface model., , , , , и . Int. J. Comput. Assist. Radiol. Surg., 14 (1): 53-61 (2019)