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A new 3D segmentation method based on the level set tech- nique is proposed. The main contribution is a robust evolutionary model which requires no fine tuning of parameters. A closed 3D surface prop- agates from an initial position towards the desired region boundaries through an iterative evolution of a specific 4D implicit function. Infor- mation about the regions is involved by estimating, at each iteration, parameters of probability density functions. The method can be applied to dierent kinds of data, e.g for segmenting anatomical structures in 3D magnetic resonance images and angiography. Experimental results of these two types of data are discussed.

Adaptive Segmentation of Multi-modal 3D Data Using Robust Level Set Techniques