Title :
Multi-subject connectivity-based parcellation of the human IPL using Gaussian mixture models and hidden Markov random fields
Author :
Wang, Eddie ; Tungaraza, Rosalia F. ; Haynor, D.R. ; Grabowski, Thomas J.
Author_Institution :
Integrated Brain Imaging Center, Univ. of Washington, Seattle, WA, USA
Abstract :
Connectivity has been proposed as a criterion for functional-anatomic segregation of cortical areas. We present a new method of characterizing the DTI-based connectivity profile of cortical voxels using Gaussian mixture models (GMMs). Parcellation of the human IPL was performed on connectivity profiles using a hidden Markov random field (HMRF) model. We applied our approach to multi-subject parcellation. Using the multisubject GMM-HMRF approach, results in a smoother segmentation of IPL that is independent of the set of subjects and visually consistent with the Juelich Atlas.
Keywords :
Gaussian processes; biodiffusion; biomedical MRI; brain; hidden Markov models; image segmentation; medical image processing; random processes; DTI-based connectivity profile; HMRF model; Juelich Atlas; cortical voxel; diffusion tensor imaging; functional-anatomic segregation; gaussian mixture model; hidden Markov random field model; human IPL parcellation; inferior pareital lobule; multisubject GMM-HMRF approach; multisubject connectivity-based parcellation; smooth IPL segmentation; Brain modeling; Gaussian mixture model; Hidden Markov models; Imaging; Joints; Measurement; Gaussian mixture model; connectivity-based parcellation; hidden Markov random fields; multisubject analysis; probabilistic tractography;
Conference_Titel :
Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4673-6456-0
DOI :
10.1109/ISBI.2013.6556526
