Use of the bootstrap technique with small training sets for computer-aided diagnosis in breast ultrasound

• Published in: Ultrasound in medicine & biology Vol. 28; no. 7; pp. 897 - 902
• Main Authors: Chen, Dar-Ren, Kuo, Wen-Jia, Chang, Ruey-Feng, Moon, Woo Kyung, Lee, Cheng Chun
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.07.2002; Elsevier
• Subjects: Adolescent; Adult; Algorithms; Biological and medical sciences; Bootstrap; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - pathology; Chi-Square Distribution; Decision Trees; Decision-tree model; Diagnosis, Computer-Assisted; Diagnosis, Differential; Female; Gynecology. Andrology. Obstetrics; Humans; Mammary gland diseases; Medical sciences; Middle Aged; Predictive Value of Tests; Sensitivity and Specificity; Tumors; Ultrasonography, Mammary - methods; Ultrasound; Bootstrap; Decision-tree model; Ultrasound; Sonography; Human; Carcinoma; Malignant tumor; Method; Decision tree; Mammary gland diseases; Accuracy; Sensitivity; Specificity; Echography; Female; Models; Diagnosis; Mammary gland; Technique; Benign neoplasm; Computer aid
• ISSN: 0301-5629; 1879-291X
• DOI: 10.1016/S0301-5629(02)00528-8

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.