Computerized Segmentation and Characterization of Breast Lesions in Dynamic Contrast-Enhanced MR Images Using Fuzzy c-Means Clustering and Snake Algorithm
Joint Authors
Peng, Yanxia
Hu, Wenyong
Li, Li
Shao, Yuanzhi
Liu, Lizhi
Pang, Yachun
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-21
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper presents a novel two-step approach that incorporates fuzzy c-means (FCMs) clustering and gradient vector flow (GVF) snake algorithm for lesions contour segmentation on breast magnetic resonance imaging (BMRI).
Manual delineation of the lesions by expert MR radiologists was taken as a reference standard in evaluating the computerized segmentation approach.
The proposed algorithm was also compared with the FCMs clustering based method.
With a database of 60 mass-like lesions (22 benign and 38 malignant cases), the proposed method demonstrated sufficiently good segmentation performance.
The morphological and texture features were extracted and used to classify the benign and malignant lesions based on the proposed computerized segmentation contour and radiologists’ delineation, respectively.
Features extracted by the computerized characterization method were employed to differentiate the lesions with an area under the receiver-operating characteristic curve (AUC) of 0.968, in comparison with an AUC of 0.914 based on the features extracted from radiologists’ delineation.
The proposed method in current study can assist radiologists to delineate and characterize BMRI lesion, such as quantifying morphological and texture features and improving the objectivity and efficiency of BMRI interpretation with a certain clinical value.
American Psychological Association (APA)
Pang, Yachun& Li, Li& Hu, Wenyong& Peng, Yanxia& Liu, Lizhi& Shao, Yuanzhi. 2012. Computerized Segmentation and Characterization of Breast Lesions in Dynamic Contrast-Enhanced MR Images Using Fuzzy c-Means Clustering and Snake Algorithm. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-486899
Modern Language Association (MLA)
Pang, Yachun…[et al.]. Computerized Segmentation and Characterization of Breast Lesions in Dynamic Contrast-Enhanced MR Images Using Fuzzy c-Means Clustering and Snake Algorithm. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-486899
American Medical Association (AMA)
Pang, Yachun& Li, Li& Hu, Wenyong& Peng, Yanxia& Liu, Lizhi& Shao, Yuanzhi. Computerized Segmentation and Characterization of Breast Lesions in Dynamic Contrast-Enhanced MR Images Using Fuzzy c-Means Clustering and Snake Algorithm. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-486899
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-486899