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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018; 21st International C Alejandro F. Frangi,Julia A. Schnabel,Gabor

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31#
發(fā)表于 2025-3-26 21:30:19 | 只看該作者
Carolina Raposo,Cristóv?o Sousa,Luis Ribeiro,Rui Melo,Jo?o P. Barreto,Jo?o Oliveira,Pedro Marques,Fe in der wissenschaftlichen Weiterbildung neben den individuellen insbesondere auch die institutionellen Adressaten in den Blick genommen werden (müssen). Nachfrageorientierung kann insofern als neuer Steuerungsmodus universit?rer Studienangebotsentwicklung bezeichnet werden, der kontr?r zu den langj
32#
發(fā)表于 2025-3-27 02:24:23 | 只看該作者
Puyang Wang,Vishal M. Patel,Ilker Hacihaliloglu in der wissenschaftlichen Weiterbildung neben den individuellen insbesondere auch die institutionellen Adressaten in den Blick genommen werden (müssen). Nachfrageorientierung kann insofern als neuer Steuerungsmodus universit?rer Studienangebotsentwicklung bezeichnet werden, der kontr?r zu den langj
33#
發(fā)表于 2025-3-27 07:02:52 | 只看該作者
A Combined Simulation and Machine Learning Approach for Image-Based Force Classification During Robos trained on images of simulated deformed sclera. We validate our approach on real OCT images collected on five . porcine eyes using a robotically-controlled needle. Results show that the applied force range can be predicted with . accuracy. Being real-time, this solution can be integrated in the co
34#
發(fā)表于 2025-3-27 13:04:08 | 只看該作者
35#
發(fā)表于 2025-3-27 16:57:22 | 只看該作者
X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgeryof the pelvic anatomy to predict 23 landmarks in single X-ray images. View independence is contingent on training conditions and, here, is achieved on a spherical segment covering 120.90. in LAO/RAO and CRAN/CAUD, respectively, centered around AP. On synthetic data, the proposed approach achieves a
36#
發(fā)表于 2025-3-27 18:12:29 | 只看該作者
37#
發(fā)表于 2025-3-28 01:37:27 | 只看該作者
38#
發(fā)表于 2025-3-28 05:21:39 | 只看該作者
DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-Guided Proceduresy and digital radiography from CT scans, tightly integrated with the software platforms native to deep learning. We use machine learning for material decomposition and scatter estimation in 3D and 2D, respectively, combined with analytic forward projection and noise injection to achieve the required
39#
發(fā)表于 2025-3-28 07:04:16 | 只看該作者
40#
發(fā)表于 2025-3-28 14:17:52 | 只看該作者
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