Diagnosis of Esophagitis Based on Deep Learning - Details

Author：

Hou, Yuling (Hou, Yuling.) | Diao, Luhong (Diao, Luhong.) | Lu, Na (Lu, Na.) | Li, Ying (Li, Ying.) | Qiao, Yong (Qiao, Yong.)

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EI Scopus

Abstract：

With　the　advent　of　the　information　age,　medical　image　classification　technology　has　become　a　hot　research　topic　in　the　field　of　computer　vision.　Based　on　the　Tensorflow　deep　learning　framework,　a　ResNet　model　of　esophagitis　disease　recognition　from　gastrointestinal　mirror　image　is　established　in　this　paper.　Further,　the　random　erasing　data　augmentation　algorithm　RE　is　applied　to　optimizing　the　images,　which　are　then　used　in　the　network.　As　a　result,　the　accuracy　of　the　optimized　network　over　the　Kvasir　data　set　can　reach　97%.　©　2021　IEEE.

Keyword：

Medical imaging Diagnosis Classification (of information) Deep learning

Author Community：

[ 1 ] [Hou, Yuling]Beijing University of Technology, College of Mathematics, Faculty of Science, Beijing, China
[ 2 ] [Diao, Luhong]Beijing University of Technology, College of Mathematics, Faculty of Science, Beijing, China
[ 3 ] [Lu, Na]Beijing University of Technology, College of Mathematics, Faculty of Science, Beijing, China
[ 4 ] [Li, Ying]Jinan Central Hospital Affiliated to Shandong University, Jinan, China
[ 5 ] [Qiao, Yong]Uniontech Co. Ltd, Beijing, China

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Source ：

Year： 2021

Page： 374-379

Language： English

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count： 1

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 5

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