Graph based spatial position mapping of low-grade gliomas

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

Volumn 6892 LNCS, Issue PART 2, 2011, Pages 508-515

  Parisot, Sarah ^a,b,c   Duffau, Hugues ^d   Chemouny, Stéphane ^c   Paragios, Nikos ^a,b  

^a ECOLE CENTRALE PARIS   (France)

^b INRIA SACLAY   (France)

^c Intrasense   (France)

^d GUI DE CHAULIAC HOSPITAL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN TUMORS; CLUSTER CENTERS; CONTENT DEPENDENCIES; CROSS VALIDATION; DIMENSIONALITY REDUCTION METHOD; GLIAL CELLS; GRAPH TOPOLOGY; GRAPH-BASED; GRAPHICAL MODEL; LEAVE-ONE-OUT; LOW-GRADE GLIOMAS; SPATIAL CLASSIFICATION; SPATIAL POSITIONS; STATISTICAL DEPENDENCIES; STATISTICAL INTERPRETATION; UNSUPERVISED CLUSTERING;

MEDICAL COMPUTING; MEDICAL IMAGING; TUMORS;

TOPOLOGY;

ALGORITHM; ARTICLE; BRAIN MAPPING; BRAIN TUMOR; COMPUTER GRAPHICS; COMPUTER SIMULATION; GLIOMA; HUMAN; IMAGE PROCESSING; METABOLISM; METHODOLOGY; NEOPLASM; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BRAIN MAPPING; BRAIN NEOPLASMS; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; GLIOMA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; NEOPLASMS;

EID: 82255181970     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23629-7_62     Document Type: Conference Paper

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