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Abstract: Transient Hemodynamics Prediction using an Efficient Octree-based Deep Learning Model., , , , , , , , и . Bildverarbeitung für die Medizin, стр. 362. Springer, (2024)Simultaneous Estimation of X-Ray Back-Scatter and Forward-Scatter Using Multi-task Learning., , , , , , , , , и . MICCAI (2), том 12262 из Lecture Notes in Computer Science, стр. 199-208. Springer, (2020)PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation., , , , , , и . CVPR, стр. 574-584. IEEE, (2023)Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model., , , , , , , , и . IPMI, том 13939 из Lecture Notes in Computer Science, стр. 183-194. Springer, (2023)Pitfalls in interventional X-ray organ dose assessment - combined experimental and computational phantom study: application to prostatic artery embolization., , , , , , , и . Int. J. Comput. Assist. Radiol. Surg., 14 (11): 1859-1869 (2019)Robust Blood Flow Velocity Estimation from 3D Rotational Angiography., , , , , , , , и . ICIP, стр. 3353-3357. IEEE, (2018)Fully-Automatic CT Data Preparation for Interventional X-Ray Skin Dose Simulation., , , , , , , , и . Bildverarbeitung für die Medizin, стр. 125-130. Springer, (2020)Pediatric Patient Surface Model Atlas Generation and X-Ray Skin Dose Estimation., , , , , , , , , и . Bildverarbeitung für die Medizin, стр. 122-127. Springer Vieweg, (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)Deep Learning Compatible Differentiable X-ray Projections for Inverse Rendering., , , , , , и . Bildverarbeitung für die Medizin, стр. 290-295. Springer, (2021)