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BioMed Research International
Volume 2013 (2013), Article ID 329046, 6 pages
http://dx.doi.org/10.1155/2013/329046
Research Article

Image Analysis of Endosocopic Ultrasonography in Submucosal Tumor Using Fuzzy Inference

1Department of Computer Engineering, Silla University, Busan 617-736, Republic of Korea
2Department of Internal Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 602-739, Republic of Korea

Received 2 June 2013; Accepted 8 July 2013

Academic Editor: Sabah Mohammed

Copyright © 2013 Kwang Baek Kim and Gwang Ha Kim. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Endoscopists usually make a diagnosis in the submucosal tumor depending on the subjective evaluation about general images obtained by endoscopic ultrasonography. In this paper, we propose a method to extract areas of gastrointestinal stromal tumor (GIST) and lipoma automatically from the ultrasonic image to assist those specialists. We also propose an algorithm to differentiate GIST from non-GIST by fuzzy inference from such images after applying ROC curve with mean and standard deviation of brightness information. In experiments using real images that medical specialists use, we verify that our method is sufficiently helpful for such specialists for efficient classification of submucosal tumors.