engleski

3-D vascular tree segmentation using level-set deformable model

This paper describes a novel 3-D level-set deformable model-based approach for segmentation of medical computed tomography (CT) images of human brain vascular tree. The method employs a 3-D edge detection method to establish the initial contours. Afterwards a velocity field is created using the gradient vector flow algorithm. The deformable model is then initialized and solved using a level-set method. Experimental validation of the method has been conducted on CT images of real patients. Comments on performance and possible improvements are discussed.

vessel tree segmentation; level-set; deformable model

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