Browse > Article
http://dx.doi.org/10.5391/JKIIS.2005.15.4.473

Analysis System of Endoscopic Image of Early Gastric Cancer  

Kim, Kwang-Baek (신라대학교 컴퓨터공학과)
Lim, Eun-Kyung (부산대학교 컴퓨터공학과)
Kim, Gwang-Ha (부산대학교 의과대학 내과학교실)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.4, 2005 , pp. 473-478 More about this Journal
Abstract
The gastric cancer takes the great part of the cancer occurrence and the mortality from cancer in Korea, and the early detection of gastric cancer is very important in the treatment and convalescence. This paper. for the early detection of gastric cancer, Proposes the analysis system of endoscopic image of the stomach that detects the abnormal region by using the change of color in the image and provides the surface tissue information to the detector. While the advanced inflammation and the cancer may be easily detected, the early inflammation and the cancer have a difficulty in detection and require the more attention lot detection. This paper, at first, converts the endoscopic image to the Image of IHb(Index of Hemoglobin) model and removes noises incurred by illumination, and next, automatically detects the regions suspected as cancer and provides the related information to the detector, or provides the surface tissue information for the regions appointed by the detector. This paper does not intend to provide the final diagnosis of the detected abnormal regions as gastric cancer, but provides the supplementary mean that reduces the load and mistaken diagnosis of the detector by automatically detecting the abnormal regions being not easily detected by human eyes and providing the additional information for the diagnosis. The experiments using practical endoscopic images for performance evaluation showed that the proposed system is effective in the analysis of endoscopic image of the stomach.
Keywords
위암;내시경 영상;암 의심 영역;IHb 채널;내시경 영상 분석;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Mitsui A, Misumi K, Murakami A, Harada K, Honmyo U, Akagi M. Endoscopic diagnosis of minute, small, and flat early gastric cancers. Endoscopy 1989;21:159-164
2 Honmyo U, Mitsui A, Murakami A, Mizumoto S, Yoshinaka I, Maeda M, et al. Mechanisms producing color change in flat early gastric cancers. Endoscopy 1997;29:366-371   DOI   ScienceOn
3 K. B. Kim, 'An Intelligent System for Recognition of Identifiers from Shipping Container Images using Fuzzy Binarization and Enhanced Hybrid Network,' Journal of Fuzzy Logic and Intelligent, Vol.14, No.3, pp. 349-356, 2004
4 Rafael Conzalez, Richard E. Woods, Digital Image Processing Second Edition, Prentice Hall
5 K. B. Kim, H. W. Yun, 'A Study on Recognition of Brochogenic Cancer Cell Image Using a New Physiological Fuzzy Neural Networks,' Japanese Journal of Medical Electronics and Biological Engineering, Vol.13, No.5, pp.39-43, 1999
6 Tsuji S, Sato N, Kawano S, et al. Functional imaging for the analysis of the mucosal blood hemoglobin distribution using electronic endoscopy. Gastrointest Endosc 1998;34:332-336   DOI   ScienceOn
7 Ogihara T, Watanabe H, Namihisa M, Sato N. Display of mucosal blood flow function and color enhancement based on blood flow index (IHb color enhancement). Clinical Gastroenterology 1997;12 :109-117
8 Kawano S, Sato N, Tsuji S, et al. Endoscopic blood flow analysis. Endoscopia Digestiva 1989;1:461-467
9 K. B. Kim, Y. J. Kim, Recognition of English Calling Cards by Using Enhanced Fuzzy Radial Basis Function Neural Networks, IEICE Trans. Fundamentals of Electronics, Communications and Computer Sciences, Vol.E87-A, No.6, pp.1355-1362, 2004