Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach

Tsung Chun Lee; Yu Huei Lin; Noriya Uedo; Hsiu Po Wang; Hsuan Ting Chang; Chung Wen Hung

doi:10.1109/EMBC.2013.6610529

Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach

Tsung Chun Lee
, Yu Huei Lin
, Noriya Uedo
, Hsiu Po Wang
, Hsuan Ting Chang
, Chung Wen Hung

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

23 Citations (Scopus)

Abstract

Gastric cancer is the fourth common cancer and the second major cause of cancer death worldwide. Early detection of gastric cancer by endoscopy surveillance is actively investigated to improve patient survival, especially using the newly developed magnifying narrow-band imaging endoscopy in the stomach. However, meticulous examination of the aforementioned images is both time and experience demanding and interpretation could be variable among different doctors, which hindered its widespread application. In this study, we developed a new image analysis system by adopting local binary pattern and vector quantization to perform pattern comparison between known training abnormal images and testing images of magnifying narrow band endoscopy images in the stomach. Our preliminary results demonstrated promising potential for automatically labeled region of interest for endoscopy doctors to focus on abnormal lesions for subsequent targeted biopsy, with the rates of recall 0.46-1.00 and precision 0.39-0.87.

Original language	English
Title of host publication	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Pages	4430-4433
Number of pages	4
DOIs	https://doi.org/10.1109/EMBC.2013.6610529
Publication status	Published - 2013
Externally published	Yes
Event	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan Duration: Jul 3 2013 → Jul 7 2013

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Other

Other	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Country/Territory	Japan
City	Osaka
Period	7/3/13 → 7/7/13

UN SDGs

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

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2013.6610529

Cite this

Lee, T. C., Lin, Y. H., Uedo, N., Wang, H. P., Chang, H. T., & Hung, C. W. (2013). Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 4430-4433). Article 6610529 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2013.6610529

Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach. / Lee, Tsung Chun; Lin, Yu Huei; Uedo, Noriya et al.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 4430-4433 6610529 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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

Lee, TC, Lin, YH, Uedo, N, Wang, HP, Chang, HT & Hung, CW 2013, Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., 6610529, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 4430-4433, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 7/3/13. https://doi.org/10.1109/EMBC.2013.6610529

Lee TC, Lin YH, Uedo N, Wang HP, Chang HT, Hung CW. Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 4430-4433. 6610529. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2013.6610529

Lee, Tsung Chun ; Lin, Yu Huei ; Uedo, Noriya et al. / Computer-aided diagnosis in endoscopy : A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. pp. 4430-4433 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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abstract = "Gastric cancer is the fourth common cancer and the second major cause of cancer death worldwide. Early detection of gastric cancer by endoscopy surveillance is actively investigated to improve patient survival, especially using the newly developed magnifying narrow-band imaging endoscopy in the stomach. However, meticulous examination of the aforementioned images is both time and experience demanding and interpretation could be variable among different doctors, which hindered its widespread application. In this study, we developed a new image analysis system by adopting local binary pattern and vector quantization to perform pattern comparison between known training abnormal images and testing images of magnifying narrow band endoscopy images in the stomach. Our preliminary results demonstrated promising potential for automatically labeled region of interest for endoscopy doctors to focus on abnormal lesions for subsequent targeted biopsy, with the rates of recall 0.46-1.00 and precision 0.39-0.87.",

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AB - Gastric cancer is the fourth common cancer and the second major cause of cancer death worldwide. Early detection of gastric cancer by endoscopy surveillance is actively investigated to improve patient survival, especially using the newly developed magnifying narrow-band imaging endoscopy in the stomach. However, meticulous examination of the aforementioned images is both time and experience demanding and interpretation could be variable among different doctors, which hindered its widespread application. In this study, we developed a new image analysis system by adopting local binary pattern and vector quantization to perform pattern comparison between known training abnormal images and testing images of magnifying narrow band endoscopy images in the stomach. Our preliminary results demonstrated promising potential for automatically labeled region of interest for endoscopy doctors to focus on abnormal lesions for subsequent targeted biopsy, with the rates of recall 0.46-1.00 and precision 0.39-0.87.

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Computer-aided diagnosis in endoscopy: A novel application toward automatic detection of abnormal lesions on magnifying narrow-band imaging endoscopy in the stomach

Abstract

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UN SDGs

ASJC Scopus subject areas

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