Connectivity-based parcellation of functional SubROIs in putamen using a sparse spatially regularized regression model
| Autor: | Martin J. McKeown, Yiming Zhang, Z. Jane Wang, Aiping Liu, Sun Nee Tan |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
0206 medical engineering Health Informatics 02 engineering and technology computer.software_genre Machine learning 03 medical and health sciences 0302 clinical medicine Lasso regression Voxel Linear regression medicine Optimization algorithm business.industry Putamen Pattern recognition Regression analysis 020601 biomedical engineering Brain region medicine.anatomical_structure Signal Processing Artificial intelligence business computer 030217 neurology & neurosurgery Neuroanatomy |
| Zdroj: | Biomedical Signal Processing and Control. 27:174-183 |
| ISSN: | 1746-8094 |
| DOI: | 10.1016/j.bspc.2016.02.005 |
| Popis: | In this paper, we present a novel framework for parcellation of a brain region into functional subROIs (Sub-Region-of-Interest) based on their connectivity patterns with other brain regions. By utilising previously established neuroanatomy information, the proposed method aims at finding spatially continuous, functionally consistent subROIs in a given brain region. The proposed framework relies on (1) a sparse spatially-regularized fused lasso regression model for encouraging spatially and functionally adjacent voxels to share similar regression coefficients; (2) an iterative merging and adaptive parameter tuning process; (3) a Graph-Cut optimization algorithm for assigning overlapped voxels into separate subROIs. Our simulation results demonstrate that the proposed method could reliably yield spatially continuous and functionally consistent subROIs. We applied the method to resting-state fMRI data obtained from normal subjects and explored connectivity to the putamen. Two distinct functional subROIs could be parcellated out in the putamen region in all subjects. This approach provides a way to extract functional subROIs that can then be investigated for alterations in connectivity in diseases of the basal ganglia, for example in Parkinson's disease. |
| Databáze: | OpenAIRE |
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