Predicting activation across individuals with resting-state functional connectivity based multi-atlas label fusion

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9350, Issue , 2015, Pages 313-320

  Langs, Georg ^a,b   Golland, Polina ^b   Ghosh, Satrajit S ^c,d  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN MAPPING; COST FUNCTIONS; FUNCTIONAL NEUROIMAGING; MEDICAL COMPUTING; MEDICAL IMAGING; NEUROIMAGING; SIGNAL SYSTEMS;

BRAIN-IMAGING DATA; EXPERIMENT CONDITION; FUNCTIONAL ACTIVATION; FUNCTIONAL SPACES; MANIFOLD ALIGNMENTS; RESTING STATE FUNCTIONAL CONNECTIVITIES; RESTING-STATE FMRI; SOURCE POPULATION;

CHEMICAL ACTIVATION;

EID: 84950989224     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-24571-3_38     Document Type: Conference Paper

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