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Titlebook: Bildverarbeitung für die Medizin 2022; Proceedings, German Klaus Maier-Hein,Thomas M. Deserno,Thomas Tolxdorf Conference proceedings 2022

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41#
發(fā)表于 2025-3-28 17:42:19 | 只看該作者
Training Deep Learning Models for 2D Spine X-rays Using Synthetic Images and Annotations Created fr. However, the availability of annotated data is often limited. To overcome such limitations, this paper addresses the idea of using synthetic spine X-ray data to train a deep learning model to aid in the detection of vertebrae. For this purpose, a pipeline for automatic generation of synthetic data
42#
發(fā)表于 2025-3-28 19:15:07 | 只看該作者
43#
發(fā)表于 2025-3-29 00:05:38 | 只看該作者
44#
發(fā)表于 2025-3-29 05:37:21 | 只看該作者
Abstract: Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffs. Medical images are often acquired in different hospitals, by different devices and using different parameters, resulting in varying intensity profiles. However, when performing population-based analysis over various datasets, e.g. from different hospitals, it is important to be able to distinguis
45#
發(fā)表于 2025-3-29 07:15:51 | 只看該作者
Abstract: Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery,ogies have been proposed to standardise the surgical workflow by localising drill sites or defining the drill tunnel orientation. A precise drill tunnel is of high clinical relevance to prevent detrimental changes in the reconstructed ligament’s biomechanics as well as early wall breakout with the r
46#
發(fā)表于 2025-3-29 11:38:24 | 只看該作者
Heads up A Study of Assistive Visualizations for Localisation Guidance in Virtual Reality, body. Providing the necessary equipment for surgeons to become accustomed to these types of devices can be expensive and time-consuming. A much more cost-effective and versatile approach to train surgeons or prepare already trained surgeons for upcoming operations is to create surgical simulations
47#
發(fā)表于 2025-3-29 16:00:15 | 只看該作者
Support Point Sets for Improving Contactless Interaction in Geometric Learning for Hand Pose Estimaeural network methods for this task usually estimate offset fields to infer the 3D joint positions. Occlusions of important hand parts and inconsistencies in the point clouds, e.g. caused by uneven exposure from the depth sensor, pose a challenge to these methods. We propose to simplify the optimiza
48#
發(fā)表于 2025-3-29 19:56:47 | 只看該作者
49#
發(fā)表于 2025-3-30 01:48:04 | 只看該作者
Towards an Islamic Restoration,s the segmentation performance by 0.33 of Dice score on the target domain compared with the baseline, and it also gives 0.28 of Dice score improvement in a more rigorous one-shot setting. Our code is available at . Few-shot-UDA.
50#
發(fā)表于 2025-3-30 04:18:00 | 只看該作者
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