Self-Trained Supervised Segmentation of Subcortical Brain Structures Using Multispectral Magnetic Resonance Images.
The aim of this paper is investigate the feasibility of automatically training supervised methods, such as k-nearest neighbor (kNN) and principal component discriminant analysis (PCDA), and to segment the four subcortical brain structures: caudate, thalamus, pallidum, and putamen. The adoption of su...
| Published in: | BioMed Research International Vol. 2015; pp. 1 - 10 |
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| Main Authors: | , , , |
| Format: | algorithm diagnostic images research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
10/25/2015
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| Online Access: | View this record in EBSCOhost |