Title :
DTI white matter fiber tractography using bayesian framework
Author_Institution :
Dept. of Electron. Eng., Chengdu Univ. of Inf. Technol., Chengdu, China
Abstract :
Diffusion tensor-MRI (DTI) White matter fiber tracking traces white matter fibber bundle and its image according to the diffusion of water molecular in the white matter. This paper uses structure information of fiber bundle and DTI information in current voxel to estimate the probability density function of the tracking direction to the next voxel. This algorithm is under the framework of Bayesian decision and uses weighted sampling to get the tracking result. Stochastic three dimension image of topologic and spatial information of white matter fiber bundle was demonstrated through multiply tracking and was applicant in real DTI data.
Keywords :
Bayes methods; biomedical MRI; decision making; medical image processing; probability; sampling methods; stochastic processes; Bayesian decision; Bayesian framework; diffusion tensor MRI; probability density function; stochastic three dimension image; weighted sampling; white matter fiber bundle; white matter fiber tracking; Bayesian methods; Diffusion tensor imaging; Ecosystems; Information technology; Magnetic resonance; Probability density function; Stochastic processes; Streaming media; Uncertainty; Underwater tracking; Bayesian framework; DTI; fiber tractography;
Conference_Titel :
E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-5514-0
DOI :
10.1109/EDT.2010.5496536