MAP segmentation of magnetic resonance images using mean field annealing

Ambalavaner Logenthiran; Wesley E. Snyder; Peter Santago II; Kerry M. Link

doi:10.1117/12.45386

1 June 1991 MAP segmentation of magnetic resonance images using mean field annealing

Ambalavaner Logenthiran, Wesley E. Snyder, Peter Santago II, Kerry M. Link

Proceedings Volume 1452, Image Processing Algorithms and Techniques II; (1991) https://doi.org/10.1117/12.45386
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

Abstract

An algorithm is described which segments magnetic resonance images while removing the noise from the images without blurring or other distortion of edges. The problem of segmentation and noise removal is posed as a restoration of an uncorrupted image, given additive white Gaussian noise and a segmentation cost. The problem is solved using a strategy called Mean Field Annealing. An a priori statistical model of the image, which includes the region classification, is chosen which drives the minimization toward solutions which are locally homogeneous and globally classified. Application of the algorithm to brain and knee images is presented.

Citation Download Citation

Ambalavaner Logenthiran, Wesley E. Snyder, Peter Santago II, and Kerry M. Link "MAP segmentation of magnetic resonance images using mean field annealing", Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); https://doi.org/10.1117/12.45386

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