Polyp Image Detection and Classification Using Deep Learning

Yao Tien Chen; Nisar Ahmad; Jin Wei Liang

doi:10.1109/ICCE-Taiwan55306.2022.9869018

Polyp Image Detection and Classification Using Deep Learning

Yao Tien Chen^*, Nisar Ahmad, Jin Wei Liang

^*Corresponding author for this work

Ming Chi University of Technology

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

2 Scopus citations

Abstract

Colorectal cancer has been one of the major mortality causes for the past decades. Colorectal polyps are the main cause of the mentioned disease and conventional polyp detection techniques are not sufficient for its proper detection. Therefore, an efficient method to detect colorectal polyps is inevitable. In this research, a deep learning method is proposed to detect and classify colorectal polyps. The polyp detection and classification are performed using YOLO algorithm. Custom dataset is also added with available dataset after obtaining colorectal images from hospital. Polyp detection and classification is enhanced by introducing custom data. Our proposed model based on YOLOV4 accurately performed the polyp detection and classification. Eventually this approach assures a valuable medical aid model.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	455-456
Number of pages	2
ISBN (Electronic)	9781665470506
DOIs	https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869018
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan Duration: 06 07 2022 → 08 07 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/Territory	Taiwan
City	Taipei
Period	06/07/22 → 08/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

colorectal cancer
custom dataset
polyp
YOLO

UN SDGs

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

Access to Document

10.1109/ICCE-Taiwan55306.2022.9869018

Cite this

Chen, Y. T., Ahmad, N., & Liang, J. W. (2022). Polyp Image Detection and Classification Using Deep Learning. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 (pp. 455-456). (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869018

Chen, Yao Tien ; Ahmad, Nisar ; Liang, Jin Wei. / Polyp Image Detection and Classification Using Deep Learning. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 455-456 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

@inproceedings{a290e8661f534a6d8905c22297ffbb15,

title = "Polyp Image Detection and Classification Using Deep Learning",

abstract = "Colorectal cancer has been one of the major mortality causes for the past decades. Colorectal polyps are the main cause of the mentioned disease and conventional polyp detection techniques are not sufficient for its proper detection. Therefore, an efficient method to detect colorectal polyps is inevitable. In this research, a deep learning method is proposed to detect and classify colorectal polyps. The polyp detection and classification are performed using YOLO algorithm. Custom dataset is also added with available dataset after obtaining colorectal images from hospital. Polyp detection and classification is enhanced by introducing custom data. Our proposed model based on YOLOV4 accurately performed the polyp detection and classification. Eventually this approach assures a valuable medical aid model.",

keywords = "colorectal cancer, custom dataset, polyp, YOLO",

author = "Chen, \{Yao Tien\} and Nisar Ahmad and Liang, \{Jin Wei\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 ; Conference date: 06-07-2022 Through 08-07-2022",

year = "2022",

doi = "10.1109/ICCE-Taiwan55306.2022.9869018",

language = "英语",

series = "Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022",

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

pages = "455--456",

booktitle = "Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022",

address = "美国",

}

Chen, YT, Ahmad, N & Liang, JW 2022, Polyp Image Detection and Classification Using Deep Learning. in Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Institute of Electrical and Electronics Engineers Inc., pp. 455-456, 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Taipei, Taiwan, 06/07/22. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869018

Polyp Image Detection and Classification Using Deep Learning. / Chen, Yao Tien; Ahmad, Nisar; Liang, Jin Wei.
Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 455-456 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

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

TY - GEN

T1 - Polyp Image Detection and Classification Using Deep Learning

AU - Chen, Yao Tien

AU - Ahmad, Nisar

AU - Liang, Jin Wei

PY - 2022

Y1 - 2022

N2 - Colorectal cancer has been one of the major mortality causes for the past decades. Colorectal polyps are the main cause of the mentioned disease and conventional polyp detection techniques are not sufficient for its proper detection. Therefore, an efficient method to detect colorectal polyps is inevitable. In this research, a deep learning method is proposed to detect and classify colorectal polyps. The polyp detection and classification are performed using YOLO algorithm. Custom dataset is also added with available dataset after obtaining colorectal images from hospital. Polyp detection and classification is enhanced by introducing custom data. Our proposed model based on YOLOV4 accurately performed the polyp detection and classification. Eventually this approach assures a valuable medical aid model.

AB - Colorectal cancer has been one of the major mortality causes for the past decades. Colorectal polyps are the main cause of the mentioned disease and conventional polyp detection techniques are not sufficient for its proper detection. Therefore, an efficient method to detect colorectal polyps is inevitable. In this research, a deep learning method is proposed to detect and classify colorectal polyps. The polyp detection and classification are performed using YOLO algorithm. Custom dataset is also added with available dataset after obtaining colorectal images from hospital. Polyp detection and classification is enhanced by introducing custom data. Our proposed model based on YOLOV4 accurately performed the polyp detection and classification. Eventually this approach assures a valuable medical aid model.

KW - colorectal cancer

KW - custom dataset

KW - polyp

KW - YOLO

UR - https://www.scopus.com/pages/publications/85138682880

U2 - 10.1109/ICCE-Taiwan55306.2022.9869018

DO - 10.1109/ICCE-Taiwan55306.2022.9869018

M3 - 会议稿件

AN - SCOPUS:85138682880

T3 - Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

SP - 455

EP - 456

BT - Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Y2 - 6 July 2022 through 8 July 2022

ER -

Chen YT, Ahmad N, Liang JW. Polyp Image Detection and Classification Using Deep Learning. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 455-456. (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). doi: 10.1109/ICCE-Taiwan55306.2022.9869018

Polyp Image Detection and Classification Using Deep Learning

Abstract

Publication series

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Bibliographical note

Keywords

UN SDGs

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