Diagnosis of Medical Image - Application of Rough Set Theory and Neural Network

• Main Author: 李昆鴻
• Other Authors: Chung-Yu Pan
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/33453518206430196132

碩士 === 東海大學 === 工業工程學系 === 91 === Nuclear medicine is a specialty that uses radioactive substance in the diagnosis and treatment of diseases. In contrast to other conventional imaging procedures, nuclear medicine imaging is unique in that it can provide both functional and structural Information of an organ simultaneously. In this study, we propose a new system that diagnoses the polar bull’s eye images based on nuclear medicine, combining rough set theory and neural network. We can get reduced patients’ textual table, which implies that the number of evaluation criteria is reduced with no information loss through rough set approach. And then, a new table which combines reduced patients’ textual table and image table is used to develop classification rules and train neural network to get rule-base and trained neural network. The effectiveness of our methodology is verified by experiments comparing neural network approach and the physician with our new system. According to the result, the specificity and the accuracy in our new system are better than neural network approach and the physician.