https://scholars.lib.ntu.edu.tw/handle/123456789/115495
標題: | Use of the Bootstrap Technique with Small Traning Sets for Computer-Aided Diagnosis in Breast Ultrasound | 作者: | Chen, Dar-Ren Kuo, Wen-Jia Chang, Ruey-Feng Moon, Woo-Kyung Lee, Cheng-Chun |
關鍵字: | Ultrasound;Bootstrap;Decision-tree model | 公開日期: | 2002 | 出版社: | 臺北市:國立臺灣大學資訊工程學系 | 起(迄)頁: | 897-902 | 來源出版物: | Ultrasound in Medicine & Biology | 摘要: | The purpose of this study was to test the efficacy of using small training sets in computer-aided diagnostic systems (CAD) and to increase the capabilities of ultrasound (US) technology in the differential diagnosis of solid breast tumors. A total of 263 sonographic images of solid breast nodules, including 129 malignancies and 134 benign nodules, were evaluated by using a bootstrap technique with 10 original training samples. Texture parameters of a region-of-interest (ROI) were resampled with a bootstrap technique and a decision-tree model was used to classify the tumor as benign or malignant. The accuracy was 87.07% (229 of 263 tumors), the sensitivity was 95.35% (123 of 129), the specificity was 79.10% (106 of 134), the positive predictive value was 81.46% (123 of 151), and the negative predictive value was 94.64% (106 of 112). This analysis method provides a second opinion for physicians with high accuracy. The new method shows a potential to be useful in future application of CAD, especially when a large database cannot be obtained for training or a newly developed ultrasonic system has smaller sets of samples. (E-mail: dlchen88@ms13.hinet.net) |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/20060927122919570874 | 其他識別: | 20060927122919570874 |
顯示於: | 資訊工程學系 |
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