Medical image segmentation using improved active contour model

In this paper, an algorithm for the semiautomatic segmentation of medical image series is proposed by combining the live wire algorithm and the active contour model. Firstly the accurate segmented results of one or more slices in a medical image series are obtained by the livewire algorithm and the watershed transform. Based on the segmentation of previous slices, the computer will segment the nearby slice using the modified active contour model automatically. To make full use of the correlative information between contiguous slices, we introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the gray-scale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows that our algorithm can obtain the boundary of the desired object from a series of medical images quickly and reliably with only little user intervention.