Conference paper
Gross segmentation of mammograms using a polynomial model
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol.3, pp.1056-1058
IEEE
Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Bridging Disciplines for Biomedicine (Amsterdam, Netherlands, 31/10/1996–03/11/1996)
1996
Abstract
The breast and background on a mammogram form complementary, connected sets. Generally, the intensities comprising the background are spatially continuous, low in value and lie within a closed interval. The background may therefore be approximated by a polynomial in x and y on the basis of the Weierstrass approximation theorem. The authors include the whole background and a small portion of the breast in the region being modelled. The modelled background is subtracted from the original image, the resulting image thresholded, and the largest low intensity region taken to be the background. Connected regions are identified, labelled and merged. The background is floodfilled, and inclusions removed from the object, to yield a breast-background binary image. The method has been tested on 58 mammograms of two views from two digital mammogram databases. With one exception, it performs well and yields a skin-air interface with sufficient fidelity to preserve a nipple in profile
Details
- Title
- Gross segmentation of mammograms using a polynomial model
- Authors/Creators
- R. Chandrasekhar (Author/Creator) - The University of Western AustraliaY. Attikiouzel (Author/Creator) - Western Sydney University
- Publication Details
- Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol.3, pp.1056-1058
- Conference
- Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Bridging Disciplines for Biomedicine (Amsterdam, Netherlands, 31/10/1996–03/11/1996)
- Publisher
- IEEE
- Identifiers
- 991005541675907891
- Copyright
- © 1996 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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