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Breast Cancer Res Treat. 2001 Mar;66(1):51-7.

Data mining with decision trees for diagnosis of breast tumor in medical ultrasonic images.

Author information

1
Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan.

Abstract

To increase the ability of ultrasonographic (US) technology for the differential diagnosis of solid breast tumors, we describe a novel computer-aided diagnosis (CADx) system using data mining with decision tree for classification of breast tumor to increase the levels of diagnostic confidence and to provide the immediate second opinion for physicians. Cooperating with the texture information extracted from the region of interest (ROI) image, a decision tree model generated from the training data in a top-down, general-to-specific direction with 24 co-variance texture features is used to classify the tumors as benign or malignant. In the experiments, accuracy rates for a experienced physician and the proposed CADx are 86.67% (78/90) and 95.50% (86/90), respectively.

PMID:
11368410
DOI:
10.1023/a:1010676701382
[Indexed for MEDLINE]

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