BOUT 发表于 2025-3-21 16:27:26
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The European Community and ASEAN,acy according to overlap size. In contrast to the conventional mosaicking approach, the proposed approach can produce panoramic image even in the case of 0% inter-cameras overlap. Additionally, the proposed approach is fast enough for clinical use.instate 发表于 2025-3-22 04:13:38
http://reply.papertrans.cn/24/2345/234468/234468_3.png记忆 发表于 2025-3-22 04:48:08
Toussaint Houeninvo,Philippe Sèdédjiution to extend ORBSLAM to be able to reconstruct a semi-dense map of soft organs. Experimental results on in-vivo pigs, shows a robust endoscope tracking even with organs deformations and partial instrument occlusions. It also shows the reconstruction density, and accuracy against ground truth surface obtained from CT.起波澜 发表于 2025-3-22 10:19:25
Preoperative Diagnostic Procedures,y deep learning, achieves a balanced accuracy of 89.6% on a real clinical dataset, outperforming the (non-real-time) state of the art by 3.8% points. The latter, a combination of deep learning with optical flow tracking, yields an average balanced accuracy of 78.2% across all the validated datasets.Transfusion 发表于 2025-3-22 14:57:15
http://reply.papertrans.cn/24/2345/234468/234468_6.pngTransfusion 发表于 2025-3-22 19:02:30
http://reply.papertrans.cn/24/2345/234468/234468_7.pngCLASP 发表于 2025-3-22 22:35:00
http://reply.papertrans.cn/24/2345/234468/234468_8.png鸣叫 发表于 2025-3-23 03:03:39
ORBSLAM-Based Endoscope Tracking and 3D Reconstruction,ution to extend ORBSLAM to be able to reconstruct a semi-dense map of soft organs. Experimental results on in-vivo pigs, shows a robust endoscope tracking even with organs deformations and partial instrument occlusions. It also shows the reconstruction density, and accuracy against ground truth surface obtained from CT.谄媚于性 发表于 2025-3-23 06:05:40
Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking,y deep learning, achieves a balanced accuracy of 89.6% on a real clinical dataset, outperforming the (non-real-time) state of the art by 3.8% points. The latter, a combination of deep learning with optical flow tracking, yields an average balanced accuracy of 78.2% across all the validated datasets.