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Titlebook: Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures; 4th International Wo M. Jorge Cardoso,Tal Arbel,Raj Shekhar Co

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樓主: gloomy
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發(fā)表于 2025-3-30 08:55:28 | 只看該作者
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發(fā)表于 2025-3-30 12:45:55 | 只看該作者
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發(fā)表于 2025-3-30 19:13:32 | 只看該作者
Towards an Automated Segmentation of the Ventro-Intermediate Thalamic NucleusMRI), in daily clinical practice. Hence, for treatment of tremor in functional neurosurgery, where the commonly used target is the Vim, the targeting procedure is done indirectly. We present a novel direct automated segmentation of the Vim using only subject-related MRI information, specifically, di
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發(fā)表于 2025-3-31 00:31:08 | 只看該作者
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發(fā)表于 2025-3-31 01:37:31 | 只看該作者
Automated Classification for Breast Cancer Histopathology Images: Is Stain Normalization Important?ng, which can be augmented by automated image analysis. In histopathology image analysis, stain normalization is an important procedure of color transfer between a source (reference) and the test image, that helps in addressing an important concern of stain color variation. In this work, we hypothes
56#
發(fā)表于 2025-3-31 05:08:41 | 只看該作者
Hybrid Tracking for Improved Registration of Laparoscopic Ultrasound and Laparoscopic Video for Augmsound images) onto live laparoscopic video. The majority of AR studies are based on either computer vision-based or hardware-based (e.g., optical and electromagnetic tracking) approaches. However, both approaches introduce registration errors because of variable operating conditions. To alleviate th
57#
發(fā)表于 2025-3-31 13:16:17 | 只看該作者
Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures4th International Wo
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發(fā)表于 2025-3-31 16:33:09 | 只看該作者
Progressive Hand-Eye Calibration for Laparoscopic Surgery Navigationuate accuracy of the proposed method, laboratory experiments were conducted by computing two errors, including forward error and backward error. The results show that the minimal forward error of 1.32?mm and backward error of 0.86 pixels were obtained at the 8. iteration. In conclusion, the high cal
59#
發(fā)表于 2025-3-31 19:06:36 | 只看該作者
Learning Camera Pose from Optical Colonoscopy Frames Through Deep Convolutional Neural Network (CNN)d the trained CNN on unseen simulated video datasets and on actual colonoscopy videos from 10 patients. Our results showed that the colonoscopy camera pose could be estimated with higher accuracy and speed than feature based computer vision methods such as the classical structure from motion (SfM) p
60#
發(fā)表于 2025-3-31 23:19:49 | 只看該作者
Motion Vector for Outlier Elimination in Feature Matching and Its Application in SLAM Based Laparoscdetect the movement of one feature point in different video frames. The outliers of feature point can be detected by enforcing a direction constraint with its MV. Our method had been implement under a SLAM-based framework for laparoscopic tracking, we modified the map management of SLAM for better l
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