MRA Fuzzy c-Means Vessel Segmentation Algorithm Based on Tubular Structure

作者：Yang J Z^*; Ma S; Tan W J; Sun Q; Cao P; Zhao D Z

来源：Journal of Medical Imaging and Health Informatics, 2015, 5(8): 1853-1858.

DOI：10.1166/jmihi.2015.1658

• Vessel Segmentation
• MRA
• Tubular Structure
• FCM

FCM (Fuzzy c-Means Algorithm, FCM) has the advantages of its unsupervised nature, the accuracy of the clustering center and its robustness to the initial conditions. Due to the noise, the blur of vascular morphology and the low contrast between target and background in MRA images, the FCM algorithm cannot get a good segmentation result. In order to solve this problem, this paper proposes an MRA fuzzy c-Means vessel segmentation algorithm based on the vascular feature. Our method combines both the tubular structure information and gray value scale information to segment cerebral vessels. Experiment results show that the proposed method can effectively extract the vessel structure and get more information of blood vessels comparing with the traditional FCM, and it has better accuracy and robustness.

• 出版日期2015-12
• 单位东北大学