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Segmentation of the fibro-glandular disc in mammograms using Gaussian mixture modelling.
- Source :
-
Medical & Biological Engineering & Computing . May2004, Vol. 42 Issue 3, p378-387. 10p. 5 Black and White Photographs, 2 Charts, 2 Graphs. - Publication Year :
- 2004
-
Abstract
- The paper presents a technique for the segmentation of the fibro-glandular disc in mammograms based upon a statistical model of breast density. The density function of the model was represented by a mixture of up to four weighted Gaussians, each one corresponding to a specific density class in the breast. The parameters of the model and the number of tissue classes in the breast were determined using the expectation-maximisation algorithm and the minimum description length method. Grey-level statistics of the pectoral muscle were used to determine the tissue categories that are likely to represent the fibro-glandular disc. The method was applied to 84 medio-lateral oblique mammograms from the Mini-MIAS database. The results of the segmented fibro-glandular disc were assessed by a radiologist using the original and the segmented images, with reference to a ranking table categorising the results of segmentation as: 1: excellent; 2: good; 3: average; 4: poor; and 5: complete failure. Of the 84 cases analysed, 64.3% were rated as excellent, 16.7% were rated as good, 10.7% were rated as average, and 4.7% were rated as poor; only 3.6% of the cases were rated as a complete failure with regard to segmentation of the fibro-glandular disc. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01400118
- Volume :
- 42
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Medical & Biological Engineering & Computing
- Publication Type :
- Academic Journal
- Accession number :
- 14048480
- Full Text :
- https://doi.org/10.1007/BF02344714