Title: Segmentation of mass in mammograms by a novel integrated active contour method

Authors: Feng Liu; Zhulin Gong; Ying Chen; Yajia Gu

Addresses: Department of Biomedical Engineering, School of Medicine, Shanghai Jiao Tong University, Chongqing Rd. 227, Shanghai, 200025, China ' Department of Biomedical Engineering, School of Medicine, Shanghai Jiao Tong University, Chongqing Rd. 227, Shanghai, 200025, China ' Department of Biomedical Engineering, School of Medicine, Shanghai Jiao Tong University, Chongqing Rd. 227, Shanghai, 200025, China ' Department of Radiology, Cancer Hospital, Fudan University, Dong'An Rd. 255, Shanghai, 200032, China

Abstract: Mass segmentation plays a vital role in the computer aided diagnosis systems for breast cancer. To efficiently detect the true boundaries of mass regions, a fully automated, dual-stage method was developed. Firstly an improved region-based level set method was applied for coarse segmentation and the gradient information was integrated to avoid boundary leaking. The obtained rough contour was used as an initial boundary for further refinement. In order to detect the delicate margins which are of significant meaning for breast diagnosis, a local geodesic active contour (LGAC) model based on local image information was proposed to refine the rough contour. The experimental results suggested that the proposed improved level set method can correctly find the radial and ambiguous edges of mass regions. Compared to the classical level set methods, the new scheme is more accurate and robust for mass segmentation in mammograms.

Keywords: mammograms; mass segmentation; level set method; boundary leaking; intensity inhomogeneity; breast cancer; local geodesic active contour; LGA; computer aided diagnosis; radial edges; ambiguous edges.

DOI: 10.1504/IJCSE.2015.071883

International Journal of Computational Science and Engineering, 2015 Vol.11 No.2, pp.207 - 215

Received: 24 Nov 2012
Accepted: 14 Apr 2013
Published online: 22 Sep 2015 *

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