Full Text:   <1415>

Summary:  <1297>

CLC number: R443+.8; TP391.4

On-line Access: 2019-11-21

Received: 2019-06-25

Revision Accepted: 2019-09-12

Crosschecked: 2019-10-08

Cited: 0

Clicked: 2185

Citations:  Bibtex RefMan EndNote GB/T7714


Di Xie


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Journal of Zhejiang University SCIENCE B 2019 Vol.20 No.12 P.1014-1020


Detection and segmentation of multi-class artifacts in endoscopy

Author(s):  Yan-yi Zhang, Di Xie

Affiliation(s):  Department of Psychology, the Children’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China; more

Corresponding email(s):   xiedi@hikvision.com

Key Words:  Endoscopic diagnosis, Detection and segmentation, Multi-class artifacts, Cascade R-CNN, PSPNet

Yan-yi Zhang, Di Xie. Detection and segmentation of multi-class artifacts in endoscopy[J]. Journal of Zhejiang University Science B, 2019, 20(12): 1014-1020.

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author="Yan-yi Zhang, Di Xie",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Detection and segmentation of multi-class artifacts in endoscopy
%A Yan-yi Zhang
%A Di Xie
%J Journal of Zhejiang University SCIENCE B
%V 20
%N 12
%P 1014-1020
%@ 1673-1581
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1900340

T1 - Detection and segmentation of multi-class artifacts in endoscopy
A1 - Yan-yi Zhang
A1 - Di Xie
J0 - Journal of Zhejiang University Science B
VL - 20
IS - 12
SP - 1014
EP - 1020
%@ 1673-1581
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1900340

Endoscopy may be used for early screening of various cancers, such as nasopharyngeal cancer, esophageal adenocarcinoma, gastric cancer, colorectal cancer, and bladder cancer, and performing minimal invasive surgical procedures, such as laparoscopy surgery. During this procedure, an endoscope is used; it is a long, thin, rigid, or flexible tube having a light source and a camera at the tip, which facilitates visualization inside the affected organs on a screen and helps doctors in diagnosis.


概要:为准确定位内窥镜视频中的人造物,帮助医生提升诊断准确率,引入深度神经网络检测与分割模型,采用特征金字塔与级联R-CNN相互结合的框架,并使用PSPNet结合分类器链的思想,从而解决分割及数据匮乏问题,有效提升性能,并在EAD 2019数据集上取得领先的性能.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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