Title :
3D Model-based method for vessel segmentation in TOF-MRA
Author :
Fang, Kui ; Wang, De-Feng ; Lui, L.M. ; Zhou, Shou-Jun ; Chu, W.C.W. ; Ahuja, A.T. ; Heng, Pheng Ann
Author_Institution :
Shenzhen Inst. of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China
Abstract :
In this paper, an automatic method to segment the blood vessel for 3D MRA (Magnetic Resonance Angiography) is presented. The segmentation process classifies MRA data into two parts: background and blood vessels. The process includes statistical model based on the voxel intensity and MRF model based on the context information of voxels. Both the models were built on 3D voxel, rather than on 2D. The proposed method is tested on the 3D Time-Of-Flight (TOF)-MRA data. The segmentation results give a good performance in extracting blood vessels.
Keywords :
biomedical MRI; blood vessels; image classification; image segmentation; medical image processing; solid modelling; statistical analysis; time of flight spectra; 3D MRA data; 3D time of flight MRA data; 3D voxel intensity; MRF model; TOF-MRA; automatic segmentation process; blood vessel segmentation; context information; magnetic resonance angiography; statistical model; Biomedical imaging; Blood vessels; Deformable models; Image segmentation; Mathematical model; Solid modeling; Three dimensional displays; Context information; Markov random field; Statistical model; Vessel segmentation;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016988
