关键词: C-V模型, 图像分割, 分水岭变换, 脑肿瘤图像

Abstract: C-V model is an effective segmentation method for medical brain tumor images. Aimed at its sensitivity to the initial contour position and time-consuming re-initialization, a new method for C-V model optimized by watershed transformation is proposed. First, the marker function is introduced, with mandatory minimum technology, to deal with the over-segmentation of traditional watershed transformation and get the coarse result. Then, the initial contour position of C-V model is confirmed based on the coarse segmentation. Finally, the C-V model without re-initialization is used for fine segmentation, obtaining the accurate segmentation. The experimental results show that the proposed method can effectively segment the common brain tumor, but also for the tumor which is attached to tissues.

Key words:  C-V model, image segmentation, watershed transformation, brain tumor image