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pro vyhledávání: '"Shetty, Karthik"'
Autor:
Shetty, Karthik, Birkhold, Annette, Egger, Bernhard, Jaganathan, Srikrishna, Strobel, Norbert, Kowarschik, Markus, Maier, Andreas
We present a novel approach for 3D human pose estimation by employing probabilistic modeling. This approach leverages the advantages of normalizing flows in non-Euclidean geometries to address uncertain poses. Specifically, our method employs normali
Externí odkaz:
http://arxiv.org/abs/2412.04665
Autor:
Shetty, Karthik, Birkhold, Annette, Jaganathan, Srikrishna, Strobel, Norbert, Egger, Bernhard, Kowarschik, Markus, Maier, Andreas
Objective: A digital twin of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless tracking, positioning, and navigation assistance in image-guided intervention
Externí odkaz:
http://arxiv.org/abs/2303.04923
Autor:
Shetty, Karthik, Birkhold, Annette, Jaganathan, Srikrishna, Strobel, Norbert, Kowarschik, Markus, Maier, Andreas, Egger, Bernhard
We introduce PLIKS (Pseudo-Linear Inverse Kinematic Solver) for reconstruction of a 3D mesh of the human body from a single 2D image. Current techniques directly regress the shape, pose, and translation of a parametric model from an input image throu
Externí odkaz:
http://arxiv.org/abs/2211.11734
Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to CT image fusion when large annotated paired datasets are available for training. However, the need for paired CT volume and X-ray images with ground truth registration
Externí odkaz:
http://arxiv.org/abs/2210.07611
Deep Learning-based 2D/3D registration methods are highly robust but often lack the necessary registration accuracy for clinical application. A refinement step using the classical optimization-based 2D/3D registration method applied in combination wi
Externí odkaz:
http://arxiv.org/abs/2107.10004
Autor:
Shetty, Karthik, Birkhold, Annette, Strobel, Norbert, Egger, Bernhard, Jaganathan, Srikrishna, Kowarschik, Markus, Maier, Andreas
Many minimally invasive interventional procedures still rely on 2D fluoroscopic imaging. Generating a patient-specific 3D model from these X-ray projection data would allow to improve the procedural workflow, e.g. by providing assistance functions su
Externí odkaz:
http://arxiv.org/abs/2102.02912
Akademický článek
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Publikováno v:
Indian Journal of Surgery. Dec2021, Vol. 83 Issue 6, p1464-1469. 6p.
Autor:
Kunaparaju, Keerthana1 (AUTHOR), Shetty, Karthik1 (AUTHOR), Jathanna, Vinod1 (AUTHOR), Nath, Kartik2 (AUTHOR), M, Roma1 (AUTHOR) roma.m@manipal.edu
Publikováno v:
Patient Safety in Surgery. 1/5/2021, Vol. 15 Issue 1, p1-4. 4p.