A three-dimensional measurement method for binocular endoscopes based on deep learning  

作　　者：Hao YU Changjiang ZHOU Wei ZHANG Liqiang WANG Qing YANG Bo YUAN 

机构地区：[1]State Key Laboratory of Modern Optical Instrumentation,College of Optical Science and Engineering,Zhejiang University,Hangzhou,310027,China [2]Research Center for Intelligent Sensing,Zhejiang Lab,Hangzhou,311100,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2022年第4期653-660,共8页信息与电子工程前沿（英文版）

基　　金：supported by the National Key Research and Development Program of China(No.2019YFC0119502);the Key Research and Development Program of Zhejiang Province,China(No.2018C03064);the Fundamental Research Funds for the Central Universities,China(No.2019FZA5016);the Zhejiang Provincial Natural Science Foundation,China(No.LGF20F050006)。

摘　　要：In the practice of clinical endoscopy,the precise estimation of the lesion size is quite significant for diagnosis.In this paper,we propose a three-dimensional(3D)measurement method for binocular endoscopes based on deep learning,which can overcome the poor robustness of the traditional binocular matching algorithm in texture-less areas.A simulated binocular image dataset is created from the target 3D data obtained by a 3D scanner and the binocular camera is simulated by 3D rendering software to train a disparity estimation model for 3D measurement.The experimental results demonstrate that,compared with the traditional binocular matching algorithm,the proposed method improves the accuracy and disparity map generation speed by 48.9%and 90.5%,respectively.This can provide more accurate and reliable lesion size and improve the efficiency of endoscopic diagnosis.

关 键 词：Binocular endoscope Three-dimensional measurement Deep learning Disparity estimation 

分 类 号：R318[医药卫生—生物医学工程] TP391.41[医药卫生—基础医学] TP18[自动化与计算机技术—计算机应用技术]