A Multigrid Approach to the Gibbsian Classification of Mammograms

Authors:
Ian R. Greenshields;Zhihong Yang
Affiliations:
-;-
Venue:
CBMS '00 Proceedings of the 13th IEEE Symposium on Computer-Based Medical Systems (CBMS'00)
Year:
2000

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Abstract

Both formal and informal locally adaptive cooling schedules have been suggested to improve the convergence rate of Gibbs (and Gibbs-like) classification algorithms. One strategy involves maintaining a global cooling schedule/visiting schedule which is turned on or off (or forcing extremal temperature values) at a site depending on the inter-iteration behavior of the classifier. This (0,1)-valued behavior of the cooling schedule is parameterized relative to the site. Here we give a preliminary discussion of a method of assigning such parameters based on a multigrid decomposition of the image. The application domain is mammography.