Please use this identifier to cite or link to this item: https://scholar.utcc.ac.th/handle/6626976254/3637
Title: A method of detecting tonsillitis images based on medical knowledge and neural network
Authors: Jirawanitcharoen, K. 
Kiattisin, S. 
Leelasantitham, A. 
Chaiprapa, P. 
Keywords: Detection;Neural network;Tonsillitis
Issue Date: 2009
Publisher: University of the Thai Chamber of Commerce
Source: K. Jirawanitcharoen, S. Kiattisin, A. Leelasantitham, P. Chaiprapa (2009) A method of detecting tonsillitis images based on medical knowledge and neural network., 125-128.
Conference: Proceedings 2009 2nd IEEE International Conference on Computer Science and Information Technology 
Abstract: Tonsillitis is a disease occurring mostly in child and adults as this disease may take to the other effects. Nowadays, a detection of tonsil grand exploits medical doctor's diagnosis to check on oral cavity. Therefore, this paper presents a method of detecting tonsillitis images based on medical knowledge and neural network (NN); as well as, the paper considers three important factors which can be indicated in swelling by the pictures in terms of a) the ratio of tonsil grand dimension, b) average of tonsil grand color and c) surface of tonsil grand as it is purulent (yes/no) using two dimensional Fast Fourier Transform (2D FFT). Finally, the three factors are inputted into NN, and samples of 30 pictures are used for training into the NN which is divided by tonsillitis patience 15 pictures and usual tonsil grand 15 pictures. In the experimental results, 20 pictures are tested to compare with the result of the medical doctor's demonstration as the result of correction approximately at 90%.
URI: https://scholar.utcc.ac.th/handle/6626976254/3637
Rights: This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.
Appears in Collections:RSO: Conference Papers

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