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A Computer-Aided Diagnosis System for Dynamic Contrast-Enhanced MR Images Based on Level Set Segmentation and ReliefF Feature Selection
Joint Authors
Pang, Zhiyong
Zhu, Dongmei
Chen, Dihu
Li, Li
Shao, Yuanzhi
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-01-06
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This study established a fully automated computer-aided diagnosis (CAD) system for the classification of malignant and benign masses via breast magnetic resonance imaging (BMRI).
A breast segmentation method consisting of a preprocessing step to identify the air-breast interfacing boundary and curve fitting for chest wall line (CWL) segmentation was included in the proposed CAD system.
The Chan-Vese (CV) model level set (LS) segmentation method was adopted to segment breast mass and demonstrated sufficiently good segmentation performance.
The support vector machine (SVM) classifier with ReliefF feature selection was used to merge the extracted morphological and texture features into a classification score.
The accuracy, sensitivity, and specificity measurements for the leave-half-case-out resampling method were 92.3%, 98.2%, and 76.2%, respectively.
For the leave-one-case-out resampling method, the measurements were 90.0%, 98.7%, and 73.8%, respectively.
American Psychological Association (APA)
Pang, Zhiyong& Zhu, Dongmei& Chen, Dihu& Li, Li& Shao, Yuanzhi. 2015. A Computer-Aided Diagnosis System for Dynamic Contrast-Enhanced MR Images Based on Level Set Segmentation and ReliefF Feature Selection. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057902
Modern Language Association (MLA)
Pang, Zhiyong…[et al.]. A Computer-Aided Diagnosis System for Dynamic Contrast-Enhanced MR Images Based on Level Set Segmentation and ReliefF Feature Selection. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1057902
American Medical Association (AMA)
Pang, Zhiyong& Zhu, Dongmei& Chen, Dihu& Li, Li& Shao, Yuanzhi. A Computer-Aided Diagnosis System for Dynamic Contrast-Enhanced MR Images Based on Level Set Segmentation and ReliefF Feature Selection. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057902
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057902