A study of CBIR(Content-based Image Retrieval) computer-aided diagnosis system of breast ultrasound images using similarity measures of distance

作     者：Kim, Min-Jeong Cho, Hyun-Chong 김민정;조현종

作者机构：Division of Electrical and Electronic Engineering Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of Interdisciplinary Graduate Program for BIT Medical Convergence Kangwon National University Korea Republic of 

出 版 物：《Transactions of the Korean Institute of Electrical Engineers》 (Trans. Korean Inst. Electr. Eng.)

年 卷 期：2017年第66卷第8期

页      面：1272-1277页

核心收录：

主　　题：Computer aided diagnosis 

摘      要：To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian(F2 family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, F2 , and Intersection family measures. Copyright © The Korean Institute of Electrical Engineers.