Automatic polyp detection in endoscopy videos: A survey

Bilal Taha; Naoufel Werghi; Jorge Dias

doi:10.2316/P.2017.852-031

Automatic polyp detection in endoscopy videos: A survey

Bilal Taha
, Naoufel Werghi
, Jorge Dias

Electrical Engineering

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

37 Scopus citations

Abstract

Early detection of polyps play an essential role for the prevention of colorectal cancer. Manual clinical inspection have many limitations and could result to either false or missed polyps. Computer aided diagnosis system has been used to help the medical expert and to provide more accurate diagnosis. Since their introduction, many types of algorithms have been proposed in the literature using different types of features and classifiers. This paper provides a state-of-the-art for the automatic detection of polyps using endoscopic videos. Given the increasing evolution of medical imaging technologies and algorithms, it is important to have a recent review in order to know the current state of the art, and the opportunities for improving existing algorithms, or developing innovative ones. The paper divides the work done on this research area according to the type of features and classification methods implemented. The features have been divided into shape, texture or fusion features. Future directions and challenges for more accurate polyp detection in endoscopy videos are also discussed.

Original language	British English
Title of host publication	Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017
Editors	Rita Kiss, Philipp J. Thurner
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	233-240
Number of pages	8
ISBN (Electronic)	9780889869905
DOIs	https://doi.org/10.2316/P.2017.852-031
State	Published - 5 Apr 2017
Event	13th IASTED International Conference on Biomedical Engineering, BioMed 2017 - Innsbruck, Austria Duration: 20 Feb 2017 → 21 Feb 2017

Publication series

Name	Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017

Conference

Conference	13th IASTED International Conference on Biomedical Engineering, BioMed 2017
Country/Territory	Austria
City	Innsbruck
Period	20/02/17 → 21/02/17

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Deep learning
Endoscopy videos
Feature fusion
Polyp detection
Shape features
Texture features

Access to Document

10.2316/P.2017.852-031

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Taha, B., Werghi, N., & Dias, J. (2017). Automatic polyp detection in endoscopy videos: A survey. In R. Kiss, & P. J. Thurner (Eds.), Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017 (pp. 233-240). Article 7893296 (Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.2316/P.2017.852-031

Taha, Bilal ; Werghi, Naoufel ; Dias, Jorge. / Automatic polyp detection in endoscopy videos : A survey. Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017. editor / Rita Kiss ; Philipp J. Thurner. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 233-240 (Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017).

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title = "Automatic polyp detection in endoscopy videos: A survey",

abstract = "Early detection of polyps play an essential role for the prevention of colorectal cancer. Manual clinical inspection have many limitations and could result to either false or missed polyps. Computer aided diagnosis system has been used to help the medical expert and to provide more accurate diagnosis. Since their introduction, many types of algorithms have been proposed in the literature using different types of features and classifiers. This paper provides a state-of-the-art for the automatic detection of polyps using endoscopic videos. Given the increasing evolution of medical imaging technologies and algorithms, it is important to have a recent review in order to know the current state of the art, and the opportunities for improving existing algorithms, or developing innovative ones. The paper divides the work done on this research area according to the type of features and classification methods implemented. The features have been divided into shape, texture or fusion features. Future directions and challenges for more accurate polyp detection in endoscopy videos are also discussed.",

keywords = "Deep learning, Endoscopy videos, Feature fusion, Polyp detection, Shape features, Texture features",

author = "Bilal Taha and Naoufel Werghi and Jorge Dias",

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Taha, B, Werghi, N & Dias, J 2017, Automatic polyp detection in endoscopy videos: A survey. in R Kiss & PJ Thurner (eds), Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017., 7893296, Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017, Institute of Electrical and Electronics Engineers Inc., pp. 233-240, 13th IASTED International Conference on Biomedical Engineering, BioMed 2017, Innsbruck, Austria, 20/02/17. https://doi.org/10.2316/P.2017.852-031

Automatic polyp detection in endoscopy videos: A survey. / Taha, Bilal; Werghi, Naoufel ; Dias, Jorge.
Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017. ed. / Rita Kiss; Philipp J. Thurner. Institute of Electrical and Electronics Engineers Inc., 2017. p. 233-240 7893296 (Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017).

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

TY - GEN

T1 - Automatic polyp detection in endoscopy videos

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AU - Taha, Bilal

AU - Werghi, Naoufel

AU - Dias, Jorge

PY - 2017/4/5

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N2 - Early detection of polyps play an essential role for the prevention of colorectal cancer. Manual clinical inspection have many limitations and could result to either false or missed polyps. Computer aided diagnosis system has been used to help the medical expert and to provide more accurate diagnosis. Since their introduction, many types of algorithms have been proposed in the literature using different types of features and classifiers. This paper provides a state-of-the-art for the automatic detection of polyps using endoscopic videos. Given the increasing evolution of medical imaging technologies and algorithms, it is important to have a recent review in order to know the current state of the art, and the opportunities for improving existing algorithms, or developing innovative ones. The paper divides the work done on this research area according to the type of features and classification methods implemented. The features have been divided into shape, texture or fusion features. Future directions and challenges for more accurate polyp detection in endoscopy videos are also discussed.

AB - Early detection of polyps play an essential role for the prevention of colorectal cancer. Manual clinical inspection have many limitations and could result to either false or missed polyps. Computer aided diagnosis system has been used to help the medical expert and to provide more accurate diagnosis. Since their introduction, many types of algorithms have been proposed in the literature using different types of features and classifiers. This paper provides a state-of-the-art for the automatic detection of polyps using endoscopic videos. Given the increasing evolution of medical imaging technologies and algorithms, it is important to have a recent review in order to know the current state of the art, and the opportunities for improving existing algorithms, or developing innovative ones. The paper divides the work done on this research area according to the type of features and classification methods implemented. The features have been divided into shape, texture or fusion features. Future directions and challenges for more accurate polyp detection in endoscopy videos are also discussed.

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KW - Shape features

KW - Texture features

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M3 - Conference contribution

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T3 - Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017

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BT - Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017

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ER -

Taha B, Werghi N , Dias J. Automatic polyp detection in endoscopy videos: A survey. In Kiss R, Thurner PJ, editors, Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 233-240. 7893296. (Proceedings of the 13th IASTED International Conference on Biomedical Engineering, BioMed 2017). doi: 10.2316/P.2017.852-031

Automatic polyp detection in endoscopy videos: A survey

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

OpenUrl availability

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