Deep learning driven colorectal lesion detection in gastrointestinal endoscopic and pathological imaging  

作　　者：Yu-Wen Cai Fang-Fen Dong Yu-Heng Shi Li-Yuan Lu Chen Chen Ping Lin Yu-Shan Xue Jian-Hua Chen Su-Yu Chen Xiong-Biao Luo 

机构地区：[1]Department of Clinical Medicine,Fujian Medical University,Fuzhou 350004,Fujian Province,China [2]Department of Medical Technology and Engineering,Fujian Medical University,Fuzhou 350004,Fujian Province,China [3]Computer Science and Engineering College,University of Alberta,Edmonton T6G 2R3,Canada [4]Endoscopy Center,Fujian Cancer Hospital,Fujian Medical University Cancer Hospital,Fuzhou 350014,Fujian Province,China [5]Department of Computer Science,Xiamen University,Xiamen 361005,Fujian,China

出　　处：《World Journal of Clinical Cases》2021年第31期9376-9385,共10页世界临床病例杂志

摘　　要：Colorectal cancer has the second highest incidence of malignant tumors and is the fourth leading cause of cancer deaths in China.Early diagnosis and treatment of colorectal cancer will lead to an improvement in the 5-year survival rate,which will reduce medical costs.The current diagnostic methods for early colorectal cancer include excreta,blood,endoscopy,and computer-aided endoscopy.In this paper,research on image analysis and prediction of colorectal cancer lesions based on deep learning is reviewed with the goal of providing a reference for the early diagnosis of colorectal cancer lesions by combining computer technology,3D modeling,5G remote technology,endoscopic robot technology,and surgical navigation technology.The findings will supplement the research and provide insights to improve the cure rate and reduce the mortality of colorectal cancer.

关 键 词：Deep learning Artificial intelligence Image analysis ENDOSCOPIC Colorectal lesions Colorectal cancer 

分 类 号：R735.34[医药卫生—肿瘤]