Breast density segmentation using texture

Authors:
Styliani Petroudi;Michael Brady
Affiliations:
Wolfson Medical Vision Laboratory, Oxford University, Oxford, United Kingdom;Wolfson Medical Vision Laboratory, Oxford University, Oxford, United Kingdom
Venue:
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Year:
2006

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Abstract

This paper describes an algorithm to segment mammo- graphic images into regions corresponding to different densities. The breast parenchymal segmentation uses information extracted for statistical texture based classification which is in turn incorporated in multi-vector Markov Random Fields. Such segmentation is key to developing quantitative mammographic analysis. The algorithm's performance is evaluated quantitatively and qualitatively and the results show the feasibility of segmenting different mammographic densities.