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Article

Quantitative Analysis of Melanosis Coli Colonic Mucosa Using Textural Patterns

1
Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan
2
Graduate Institute of Library, Information and Archival Studies, National Chengchi University, Taipei 116, Taiwan
3
Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 106, Taiwan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(1), 404; https://doi.org/10.3390/app10010404
Submission received: 1 October 2019 / Revised: 26 December 2019 / Accepted: 2 January 2020 / Published: 5 January 2020
(This article belongs to the Special Issue Image Processing Techniques for Biomedical Applications)

Abstract

Melanosis coli (MC) is a disease related to long-term use of anthranoid laxative agents. Patients with clinical constipation or obesity are more likely to use these drugs for long periods. Moreover, patients with MC are more likely to develop polyps, particularly adenomatous polyps. Adenomatous polyps can transform to colorectal cancer. Recognizing multiple polyps from MC is challenging due to their heterogeneity. Therefore, this study proposed a quantitative assessment of MC colonic mucosa with texture patterns. In total, the MC colonoscopy images of 1092 person-times were included in this study. At the beginning, the correlations among carcinoembryonic antigens, polyp texture, and pathology were analyzed. Then, 181 patients with MC were extracted for further analysis while patients having unclear images were excluded. By gray-level co-occurrence matrix, texture patterns in the colorectal images were extracted. Pearson correlation analysis indicated five texture features were significantly correlated with pathological results (p < 0.001). This result should be used in the future to design an instant help software to help the physician. The information of colonoscopy and image analystic data can provide clinicians with suggestions for assessing patients with MC.
Keywords: gray-level co-occurrence matrix; melanosis coli; colon adenoma gray-level co-occurrence matrix; melanosis coli; colon adenoma

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MDPI and ACS Style

Lo, C.-M.; Chen, C.-C.; Yeh, Y.-H.; Chang, C.-C.; Yeh, H.-J. Quantitative Analysis of Melanosis Coli Colonic Mucosa Using Textural Patterns. Appl. Sci. 2020, 10, 404. https://doi.org/10.3390/app10010404

AMA Style

Lo C-M, Chen C-C, Yeh Y-H, Chang C-C, Yeh H-J. Quantitative Analysis of Melanosis Coli Colonic Mucosa Using Textural Patterns. Applied Sciences. 2020; 10(1):404. https://doi.org/10.3390/app10010404

Chicago/Turabian Style

Lo, Chung-Ming, Chun-Chang Chen, Yu-Hsuan Yeh, Chun-Chao Chang, and Hsing-Jung Yeh. 2020. "Quantitative Analysis of Melanosis Coli Colonic Mucosa Using Textural Patterns" Applied Sciences 10, no. 1: 404. https://doi.org/10.3390/app10010404

APA Style

Lo, C.-M., Chen, C.-C., Yeh, Y.-H., Chang, C.-C., & Yeh, H.-J. (2020). Quantitative Analysis of Melanosis Coli Colonic Mucosa Using Textural Patterns. Applied Sciences, 10(1), 404. https://doi.org/10.3390/app10010404

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