Using multiparametric data with missing features for learning patterns of pathology

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

Volumn 7512 LNCS, Issue , 2012, Pages 468-475

  Ingalhalikar, Madhura ^a   Parker, William A ^a   Bloy, Luke ^a   Roberts, Timothy P L ^b   Verma, Ragini ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b CHILDREN S HOSPITAL OF PHILADELPHIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN MAPPING; DIFFUSION TENSOR IMAGING; MAGNETIC RESONANCE IMAGING; MAGNETOENCEPHALOGRAPHY; MEDICAL COMPUTING; PATHOLOGY; TENSORS;

AUTISM SPECTRUM DISORDERS; FUNCTIONAL FEATURES; INDIVIDUAL CLASSIFIERS; MULTIMODAL CLASSIFIERS; MULTIPLE IMAGING MODALITY; PROBABILISTIC SCORES; SPATIO-TEMPORAL DATASET; STRUCTURAL CONNECTIVITY;

CLASSIFICATION (OF INFORMATION);

ADOLESCENT; ALGORITHM; ARTICLE; AUTISM; AUTOMATED PATTERN RECOGNITION; BRAIN; BRAIN MAPPING; CHILD; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFANT; MAGNETOENCEPHALOGRAPHY; MALE; METHODOLOGY; NEWBORN; PATHOLOGY; PRESCHOOL CHILD;

ADOLESCENT; ALGORITHMS; BRAIN; BRAIN MAPPING; CHILD; CHILD DEVELOPMENT DISORDERS, PERVASIVE; CHILD, PRESCHOOL; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFANT; INFANT, NEWBORN; MAGNETOENCEPHALOGRAPHY; MALE; PATTERN RECOGNITION, AUTOMATED; SUBTRACTION TECHNIQUE;

MLCS; MLOWN;

EID: 84872924682     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33454-2_58     Document Type: Conference Paper

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