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Proceedings Paper

Image enhancement and edge-based mass segmentation in mammogram
Author(s): Yu Zhang; Noriko Tomuro; Jacob Furst; Daniela Stan Raicu
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Paper Abstract

This paper presents a novel, edge-based segmentation method for identifying the mass contour (boundary) for a suspicious mass region (Region of Interest (ROI)) in a mammogram. The method first applies a contrast stretching function to adjust the image contrast, then uses a filtering function to reduce image noise. Next, for each pixel in a ROI, the energy descriptor (one of the Haralick descriptors) is computed from the co-occurrence matrix of the pixel; and the energy texture image of a ROI is obtained. From the energy texture image, the edges in the image are detected; and the mass region is identified from the closed-path edges. Finally, the boundary of the identified mass region is used as the contour of the segmented mass. We applied our method to ROI-marked mammogram images from the Digital Database for Screening Mammography (DDSM). Preliminary results show that the contours detected by our method outline the shape and boundary of a mass much more closely than the ROI markings made by radiologists.

Paper Details

Date Published: 13 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76234P (13 March 2010); doi: 10.1117/12.844492
Show Author Affiliations
Yu Zhang, DePaul Univ. (United States)
Noriko Tomuro, DePaul Univ. (United States)
Jacob Furst, DePaul Univ. (United States)
Daniela Stan Raicu, DePaul Univ. (United States)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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