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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023; 26th International C Hayit Greenspan,Anant Madabhushi,Russell Tay

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31#
發(fā)表于 2025-3-27 00:29:55 | 只看該作者
A Novel Video-CTU Registration Method with Structural Point Similarity for FURS Navigationeo-CTU registration optimization. We evaluate our video-CTU registration method on in-house ureteroscopic data acquired from the operating room, with the experimental results showing that our method attains higher accuracy than current methods. Particularly, it can reduce the position and orientatio
32#
發(fā)表于 2025-3-27 01:46:21 | 只看該作者
33#
發(fā)表于 2025-3-27 08:39:00 | 只看該作者
TCL: Triplet Consistent Learning for Odometry Estimation of Monocular Endoscope adding extra model parameters. Experiments on public datasets demonstrate that TCL effectively improves the accuracy of unsupervised methods even with limited number of training samples. Code is available at ..
34#
發(fā)表于 2025-3-27 13:00:44 | 只看該作者
Regressing Simulation to?Real: Unsupervised Domain Adaptation for?Automated Quality Assessment in?Trncertainty of feature statistics in the real domain and diversifies simulated images with style variants extracted from the real images, alleviating the domain gap. We enforce SCL and TL across different real-stylized variants to learn domain-invariant and task-specific representations. Experimental
35#
發(fā)表于 2025-3-27 16:19:11 | 只看該作者
Estimated Time to?Surgical Procedure Completion: An Exploration of?Video Analysis Methodsing video datasets for Appendectomy and RARP. Even though AI-based applications are ubiquitous in many domains of our lives, some industries are still lagging behind. Specifically, today, ETC is still done by a mere average of a surgeon’s past timing data without considering the visual data captured
36#
發(fā)表于 2025-3-27 20:52:54 | 只看該作者
A Transfer Learning Approach to?Localising a?Deep Brain Stimulation?Targeton clinical-quality data. The approach transfers anatomical information from publicly available high-quality datasets to a wide range of white matter connectivity features in low-quality data, to augment inference on the Vim. We demonstrate that the approach can robustly and reliably identify the Vi
37#
發(fā)表于 2025-3-28 00:16:51 | 只看該作者
38#
發(fā)表于 2025-3-28 03:14:40 | 只看該作者
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發(fā)表于 2025-3-28 09:59:30 | 只看該作者
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發(fā)表于 2025-3-28 13:00:23 | 只看該作者
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