A multigrid approach to the Gibbsian classification of mammograms

Author

Greenshields, Ian R. ; Yang, Zhihong

Author_Institution

Dept. of Comput. Sci. & Eng., Connecticut Univ., CT, USA

fYear

2000

fDate

2000

Firstpage

169

Lastpage

173

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 interiteration behaviour of the classifier. This (0,1)-valued behaviour of the cooling schedule is parameterized relative to the site. 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

Keywords

convergence of numerical methods; image classification; mammography; medical image processing; (0,1)-valued behaviour; Gibbs classification algorithms; convergence rate; formal locally-adaptive cooling schedules; global cooling schedule/visiting schedule; informal locally-adaptive cooling schedules; interiteration behaviour; mammograms; multigrid image decomposition; Convergence; Cooling; Geometry; Sampling methods; Temperature dependence; Temperature distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2000. CBMS 2000. Proceedings. 13th IEEE Symposium on

Conference_Location

Houston, TX

ISSN

1063-7125

Print_ISBN

0-7695-0484-1

Type

conf

DOI

10.1109/CBMS.2000.856895

Filename

856895