Cerebrovascular egmentation based on region growing and level set algorithm
Xie Li-Zhi, Mingquan Zhou, Tian Yun, Rong-Fei Cao · 2012
This paper proposed a cerebrovascular segmentation model based on region growing and level set. Firstly, a statistics and region growing model is used to detect the vessel region. During the process, a Maximum Intensity Projection (MIP) image from volume data is segmented by Otsu algorithm to get the seeds, and then to get the contour of vessel by an improved region growing algorithm. Moreover, an improved local-adaptive level set method is developed to implement the accurate segmentation. It can be seen from the results that this hybrid segmentation algorithm is more accurate than the general level set algorithm, especially segmented the vessels with small radius.