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Non-local atlas-guided multi-channel forest learning for human brain labeling
Guangkai Ma
, Yaozong Gao
, Guorong Wu
, Ligang Wu
, Dinggang Shen
Research output
:
Chapter in Book/Report/Conference proceeding
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Conference contribution
1
Citation (Scopus)
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Dive into the research topics of 'Non-local atlas-guided multi-channel forest learning for human brain labeling'. Together they form a unique fingerprint.
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Keyphrases
Anatomical Structure
33%
Appearance Features
33%
Appearance Information
33%
Brain Labeling
100%
Brain MR Image
33%
Brain Research
33%
Complex Scenes
33%
Computer Vision
33%
Context Features
66%
Fusion Method
66%
High-Level Context
33%
Human Brain
100%
Hybrid Features
33%
Inter-subject Variation
33%
Label Fusion
100%
Learning-based
66%
Multi-atlas
33%
Multi-channel
100%
Nonlinear Relationship
33%
Random Forest
66%
State-of-the-art Techniques
33%
Target Image
66%
Target Labels
33%
Computer Science
Brain Research
50%
Computer Vision
50%
Existing Label
50%
Random Decision Forest
100%