Speed and efficiency analysis of artificial intelligence recognition system of glomerular pathology based on Faster R-CNN algorithm

Speed and efficiency analysis of artificial intelligence recognition system of glomerular pathology based on Faster R-CNN algorithm

Objective To develop an artificial intelligence(AI) system that can automatically identify the glomerulus in the images of renal histopathological sections, helping pathologists to improve the speed and efficiency of calculating the number of glomerulus and identifying ischaemia-sclerosing glomerulu...

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Bibliographic Details
Main Authors: YANG Hui, ZHANG Xing-na, JIANG Qiu-zhu, YUAN Cheng-ying, QU Chong-xiao, LIU Yun-xiao, WANG Chen, LI Ming, LI Rong-shan, ZHOU Xiao-shuang
Format: Article
Language:zho
Published: Editorial Department of Journal of Clinical Nephrology 2020-01-01
Series:Linchuang shenzangbing zazhi
Subjects:
Big data
Artificial intelligence
Faster R-CNN
Renal pathology image
Glomerulus
Online Access:http://www.lcszb.com/thesisDetails?columnId=57909265&Fpath=home&index=0
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