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A number of methods based on geometric deformable models have been proposed recently to segment medical images. These methods require the definition of a speed function that governs model deformation. In this paper we propose a new speed function that is modified dynamically as the front progresses. This new speed function is particularly well adapted to situations where edges are ill-defined, adjacent structures have comparable intensity values, and images are noisy. We illustrate qualitatively the performance of our approach on a variety of MR, CT, and ultrasound images. The examples show the generality of our approach and its insensitivity to parameters. We also evaluate it quantitatively on several CT scans of the liver.

Robust Segmentation of Medical Images Using Geometric Deformable Models and a Dynamic Speed Function