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Image Analysis of Endosocopic Ultrasonography in Submucosal Tumor Using Fuzzy Inference
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-18
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Kim, Kwang Baek& Kim, Gwang Ha. 2013. Image Analysis of Endosocopic Ultrasonography in Submucosal Tumor Using Fuzzy Inference. BioMed Research International،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1004038
Modern Language Association (MLA)
Kim, Kwang Baek& Kim, Gwang Ha. Image Analysis of Endosocopic Ultrasonography in Submucosal Tumor Using Fuzzy Inference. BioMed Research International No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1004038
American Medical Association (AMA)
Kim, Kwang Baek& Kim, Gwang Ha. Image Analysis of Endosocopic Ultrasonography in Submucosal Tumor Using Fuzzy Inference. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1004038
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1004038