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Main Author:	Zhu, Yicheng
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2501.01465
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author	Zhu, Yicheng
author_facet	Zhu, Yicheng
contents	Tracking surgical modifications based on endoscopic videos is technically feasible and of great clinical advantages; however, it still remains challenging. This report presents a modular pipeline to divide and conquer the clinical challenges in the process. The pipeline integrates frame selection, depth estimation, and 3D reconstruction components, allowing for flexibility and adaptability in incorporating new methods. Recent advancements, including the integration of Depth-Anything V2 and EndoDAC for depth estimation, as well as improvements in the Iterative Closest Point (ICP) alignment process, are detailed. Experiments conducted on the Hamlyn dataset demonstrate the effectiveness of the integrated methods. System capability and limitations are both discussed.
format	Preprint
id	arxiv_https___arxiv_org_abs_2501_01465
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS Zhu, Yicheng Image and Video Processing Computer Vision and Pattern Recognition Tracking surgical modifications based on endoscopic videos is technically feasible and of great clinical advantages; however, it still remains challenging. This report presents a modular pipeline to divide and conquer the clinical challenges in the process. The pipeline integrates frame selection, depth estimation, and 3D reconstruction components, allowing for flexibility and adaptability in incorporating new methods. Recent advancements, including the integration of Depth-Anything V2 and EndoDAC for depth estimation, as well as improvements in the Iterative Closest Point (ICP) alignment process, are detailed. Experiments conducted on the Hamlyn dataset demonstrate the effectiveness of the integrated methods. System capability and limitations are both discussed.
title	Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS
topic	Image and Video Processing Computer Vision and Pattern Recognition
url	https://arxiv.org/abs/2501.01465

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