Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a -spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. -- The potential fields are initially designed based on the spatial features of the edges in the ...

• Type: Journal
• Year: 2002
• Where: TMI
• Authors: Alain Pitiot, Arthur W. Toga, Paul M. Thompson
• Keywords: Image, Potential Fields, Target Structure, TMI 2002