Gastric Cancer Diagnosis with Mask R-CNN

Guitao Cao; Wenli Song; Zhenwei Zhao

doi:10.1109/IHMSC.2019.00022

Gastric Cancer Diagnosis with Mask R-CNN

Guitao Cao
, Wenli Song
, Zhenwei Zhao

Software Engineering Institute

East China Normal University
Shandong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

34 Scopus citations

Abstract

It is a reliable way to judge gastric cancer by pathological section. Using deep learning method to detect medical images, as an auxiliary diagnosis method, it can improve the speed and accuracy of doctors to diagnose gastric cancer, and reduce misdiagnosis and missed diagnosis. Mask R-CNN is the latest method in the related field at the beginning of the research. It is mainly used to segment the objects in daily life and achieve good results. The medical image is very different from the scene in life, and the detection effect is also weakened. We use the Mask R-CNN method to detect the pathological sections of gastric cancer, and segment the cancer nest, and then optimize it by adjusting parameters. The method finally allows it to obtain a test result with an AP value of 61.2 when detecting medical images.

Original language	English
Title of host publication	Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	60-63
Number of pages	4
ISBN (Electronic)	9781728118598
DOIs	https://doi.org/10.1109/IHMSC.2019.00022
State	Published - Aug 2019
Event	11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019 - Hangzhou, China Duration: 24 Aug 2019 → 25 Aug 2019

Publication series

Name	Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
Volume	1

Conference

Conference	11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
Country/Territory	China
City	Hangzhou
Period	24/08/19 → 25/08/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Gastric Cancer
Instance Segmentation
Mask R-CNN
Pathological Section

Access to Document

10.1109/IHMSC.2019.00022

Cite this

Cao, G., Song, W., & Zhao, Z. (2019). Gastric Cancer Diagnosis with Mask R-CNN. In Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019 (pp. 60-63). Article 8941531 (Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IHMSC.2019.00022

Cao, Guitao ; Song, Wenli ; Zhao, Zhenwei. / Gastric Cancer Diagnosis with Mask R-CNN. Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 60-63 (Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019).

@inproceedings{f19478aade34492ab7c3f0a7997ea1ee,

title = "Gastric Cancer Diagnosis with Mask R-CNN",

abstract = "It is a reliable way to judge gastric cancer by pathological section. Using deep learning method to detect medical images, as an auxiliary diagnosis method, it can improve the speed and accuracy of doctors to diagnose gastric cancer, and reduce misdiagnosis and missed diagnosis. Mask R-CNN is the latest method in the related field at the beginning of the research. It is mainly used to segment the objects in daily life and achieve good results. The medical image is very different from the scene in life, and the detection effect is also weakened. We use the Mask R-CNN method to detect the pathological sections of gastric cancer, and segment the cancer nest, and then optimize it by adjusting parameters. The method finally allows it to obtain a test result with an AP value of 61.2 when detecting medical images.",

keywords = "Gastric Cancer, Instance Segmentation, Mask R-CNN, Pathological Section",

author = "Guitao Cao and Wenli Song and Zhenwei Zhao",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019 ; Conference date: 24-08-2019 Through 25-08-2019",

year = "2019",

month = aug,

doi = "10.1109/IHMSC.2019.00022",

language = "英语",

series = "Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "60--63",

booktitle = "Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019",

address = "美国",

}

Cao, G, Song, W & Zhao, Z 2019, Gastric Cancer Diagnosis with Mask R-CNN. in Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019., 8941531, Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 60-63, 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019, Hangzhou, China, 24/08/19. https://doi.org/10.1109/IHMSC.2019.00022

Gastric Cancer Diagnosis with Mask R-CNN. / Cao, Guitao; Song, Wenli; Zhao, Zhenwei.
Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 60-63 8941531 (Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Gastric Cancer Diagnosis with Mask R-CNN

AU - Cao, Guitao

AU - Song, Wenli

AU - Zhao, Zhenwei

PY - 2019/8

Y1 - 2019/8

N2 - It is a reliable way to judge gastric cancer by pathological section. Using deep learning method to detect medical images, as an auxiliary diagnosis method, it can improve the speed and accuracy of doctors to diagnose gastric cancer, and reduce misdiagnosis and missed diagnosis. Mask R-CNN is the latest method in the related field at the beginning of the research. It is mainly used to segment the objects in daily life and achieve good results. The medical image is very different from the scene in life, and the detection effect is also weakened. We use the Mask R-CNN method to detect the pathological sections of gastric cancer, and segment the cancer nest, and then optimize it by adjusting parameters. The method finally allows it to obtain a test result with an AP value of 61.2 when detecting medical images.

AB - It is a reliable way to judge gastric cancer by pathological section. Using deep learning method to detect medical images, as an auxiliary diagnosis method, it can improve the speed and accuracy of doctors to diagnose gastric cancer, and reduce misdiagnosis and missed diagnosis. Mask R-CNN is the latest method in the related field at the beginning of the research. It is mainly used to segment the objects in daily life and achieve good results. The medical image is very different from the scene in life, and the detection effect is also weakened. We use the Mask R-CNN method to detect the pathological sections of gastric cancer, and segment the cancer nest, and then optimize it by adjusting parameters. The method finally allows it to obtain a test result with an AP value of 61.2 when detecting medical images.

KW - Gastric Cancer

KW - Instance Segmentation

KW - Mask R-CNN

KW - Pathological Section

UR - https://www.scopus.com/pages/publications/85078279461

U2 - 10.1109/IHMSC.2019.00022

DO - 10.1109/IHMSC.2019.00022

M3 - 会议稿件

AN - SCOPUS:85078279461

T3 - Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

SP - 60

EP - 63

BT - Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

Y2 - 24 August 2019 through 25 August 2019

ER -

Cao G, Song W, Zhao Z. Gastric Cancer Diagnosis with Mask R-CNN. In Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 60-63. 8941531. (Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019). doi: 10.1109/IHMSC.2019.00022

Gastric Cancer Diagnosis with Mask R-CNN

Abstract

Publication series

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UN SDGs

Keywords

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