AI based colorectal disease detection using real-time screening colonoscopy  

作　　者：Jiawei Jiang Qianrong Xie Zhuo Cheng Jianqiang Cai Tian Xia Hang Yang Bo Yang Hui Peng Xuesong Bai Mingque Yan Xue Li Jun Zhou Xuan Huang Liang Wang Haiyan Long Pingxi Wang Yanpeng Chu Fan-Wei Zeng Xiuqin Zhang Guangyu Wang Fanxin Zeng 

机构地区：[1]Department of Clinical Research Center,Dazhou Central Hospital,Dazhou 635000,China [2]Department of Computer Science,Eidgenossische Technische Hochschule Zurich,Zurich 999034,Switzerland [3]Digestive endoscopy center,Dazhou Central Hospital,Dazhou 635000,China [4]Department of Hepatobiliary Surgery,National Cancer Center/Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100730,China [5]National Center of Biomedical Analysis,Beijing 100850,China [6]College of Informatics,Huazhong Agricultural University,Wuhan 430070,China [7]Department of Ophthalmology,Medical Research Center,Beijing Chao-Yang Hospital,Capital Medical University,Beijing 100020,China [8]Information Department,Dazhou Central Hospital,Dazhou 635000,China [9]Digestive endoscopy center,Quxian People’s Hospital,Dazhou 635000,China [10]Institute of Molecular Medicine,Peking University,Beijing 100871,China [11]State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China [12]Department of Medicine,Sichuan University of Arts and Science,Dazhou 635000,China

出　　处：《Precision Clinical Medicine》2021年第2期109-118,共10页精准临床医学（英文）

基　　金：This study was funded by the National Natural Science Foundation of China(Grant No.81902861 to F.Z.and 32000485 to X.H.);“Xinglin Scholars”Scientific Research Project Fund of Chengdu University of Traditional Chinese Medicine(Grant No.YYZX2019012 to F.Z.);the Scientific Research Fund of Technology Bureau in Dazhou(Grant No.17YYJC0004 to F.-W.Z.);the Key Research and Development Project Fund of Science and Technology Bureau in Dazhou,Sichuan Province(Grant No.20ZDYF0001 to F.-W.Z.).We express our deepest appreciation to J.Z,Y.C.for organizing the raw data and G.Y.for the revising the manuscript.

摘　　要：Colonoscopy is an effective tool for early screening of colorectal diseases.However,the application of colonoscopy in distinguishing different intestinal diseases still faces great challenges of efficiency and accuracy.Here we constructed and evaluated a deep convolution neural network(CNN)model based on 117055 images from 16004 individuals,which achieved a high accuracy of 0.933 in the validation dataset in identifying patients with polyp,colitis,colorectal cancer(CRC)from normal.The proposed approach was further validated onmulti-center real-time colonoscopy videos and images,which achieved accurate diagnostic performance on detecting colorectal diseases with high accuracy and precision to generalize across external validation datasets.The diagnostic performance of the model was further compared to the skilled endoscopists and the novices.In addition,our model has potential in diagnosis of adenomatous polyp and hyperplastic polyp with an area under the receiver operating characteristic curve of 0.975.Our proposed CNN models have potential in assisting clinicians in making clinical decisions with efficiency during application.

关 键 词：artificial intelligence(AI) colorectal disease real-time colonoscopy 

分 类 号：R73[医药卫生—肿瘤]