Segmentation of magnetic resonance images using mean field annealing

摘要

The problem of segmentation of magnetic resonance images into regions of uniform tissue density is posed as an optimization problem. An objective function is defined, and the resulting minimization problem is solved using mean field annealing a technique which usually finds the global minimum in non-convex optimization problems and performs particularly well on images. Noise sensitivity is evaluated by tests on synthetic images, and the technique is then applied to clinical images of a brain and a knee. The technique shows promise as a method for quantitatively monitoring change.