The algorithm of stereo vision and shape from shading based on endoscope imaging

计算机科学 人工智能 计算机视觉 稳健性(进化) 三维重建 侵入性外科 立体视觉 接头(建筑物) 医学 外科 建筑工程 生物化学 化学 工程类 基因
作者
Ziyi Cao,Yaxiang Wang,Wenfeng Zheng,Lirong Yin,Yushan Tang,Miao Wang,Shan Liu,Bo Yang
出处
期刊:Biomedical Signal Processing and Control [Elsevier]
卷期号:76: 103658-103658 被引量:72
标识
DOI:10.1016/j.bspc.2022.103658
摘要

With medical endoscopic equipment development, minimally invasive surgery (MIS) has gradually become an essential technical means in daily medical practice. In recent years, minimally invasive surgery has been widely used because of its small incision and quick recovery. However, at the same time, minimally invasive surgery has put forward higher requirements for the operator. A 3D reconstruction framework combined with stereo vision and Shape from Shading (SFS) was proposed to improve endoscopic imaging accuracy and reduce the difficulty of minimally invasive surgery. This paper constructs a joint objective function based on the improved SFS and the classical stereo matching method. The optimization algorithm of the depth map under the joint objective function is given. Finally, the experimental verification of the joint reconstruction algorithm is carried out. The joint reconstruction framework's effectiveness is verified by qualitative and quantitative comparison and analysis based on the silica-gel-heart model and real-heart image datasets. The experimental results show that the joint reconstruction framework can restore the heart surface shape as a whole and retain the local details. Compared with the classical stereo vision and SFS methods, the proposed joint reconstruction method has better robustness and reconstruction accuracy.

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