Accession number:20082311296562
Title:Computer-aided diagnosis of breast color elastography
Authors:Chang, Ruey-Feng (1); Shen, Wei-Chih (2); Yang, Min-Chun (1); Moon, Woo Kyung (3); Takada, Etsuo (4); Ho, Yu-Chun (5);
Nakajima, Michiko (6); Kobayashi, Masayuki (6)
Author affiliation:(1) Department of Computer Science and Information Engineering, Graduate Institute of Biomedical
Electronics and Bioinformatics, National Taiwan University, Taipei, 10617, Taiwan; (2) Department of Computer Science and
Information Engineering, Asia University, Taichung County, 41354, Taiwan; (3) Department of Diagnostic Radiology, College of
Medicine, Seoul National University Hospital, Korea, Republic of; (4) Center of Medical Ultrasonics, Dokkyo Medical University, Mibu, Japan; (5) Department of Computer Science and Information
Engineering, National Chung Cheng University, Chiayi, 621, Taiwan;
(6) Comprehensive Regional Service, Saitama Medical University, Saitama 350-0495, Japan
Corresponding author:Chang, R.-F.
(rfchany@csie.ntu.edu.tw)
Source title:Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Abbreviated source title:Progr. Biomed. Opt. Imaging Proc. SPIE Volume:6915
Monograph title:Medical Imaging 2008 - Computer-Aided Diagnosis Issue date:2008
Publication year:2008 Article number:69150I Language:English ISSN:16057422
ISBN-13:9780819470997
Document type:Conference article (CA)
Conference name:Medical Imaging 2008 - Computer-Aided Diagnosis Conference date:Febrary 19, 2008 - Febrary 21, 2008
Conference location:San Diego, CA, United states Conference code:72129
Sponsor:The International Society for Optical Engineering (SPIE) Publisher:SPIE, P.O. Box 10, Bellingham WA, WA 98227-0010, United
States
Abstract:Ultrasound has been an important imaging technique for detecting breast tumors. As opposed to the conventional B- mode image, the ultrasound elastography is a new technique for imaging the elasticity and applied to detect the stiffness of tissues. The red region of color elastography indicates the soft tissue and the blue one indicates the hard tissue, and the harder tissue usually is classified to malignancy. In this paper, we proposed a CAD system on elastography to measure whether this system is effective and accurate to classify the tumor into benign and malignant. According to the features of elasticity, the color elastography was transferred to HSV color space and extracted meaningful features from hue images. Then the neural network was utilized in multiple features to distinguish tumors. In this experiment, there are 180 pathology- proven cases including 113 benign and 67 malignant cases used to examine the classification. The results of the proposed system showed an accuracy of 83.89%, a sensitivity of 85.07% and a specificity of 83.19%. Compared with the physician's diagnosis, an accuracy of 78.33%, a sensitivity of 53.73% and a specificity of 92.92%, the proposed CAD system had better performance.
Moreover, the agreement of the proposed CAD system and the physician's diagnosis was calculated by kappa statistics, the kappa 0.54 indicated there is a moderate agreement of observers.
Number of references:19 Main heading:Tumors
Controlled terms:Computer aided diagnosis - Neural networks - Pathology - Tissue culture - Ultrasonic imaging
Uncontrolled terms:Breast color elastography - Kappa statistics Classification code:461.1 Biomedical Engineering - 461.2 Biological Materials and Tissue Engineering - 461.6 Medicine and
Pharmacology - 723.5 Computer Applications - 753.1 Ultrasonic Waves
DOI:10.1117/12.769617 Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
