Joint segmentation and deformable registration of brain scans guided by a tumor growth model

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 532-540

  Gooya, Ali ^a   Pohl, Kilian M ^a   Bilello, Michel ^a   Biros, George ^a   Davatzikos, Christos ^a  

^a Section for Biomedical Image Analysis   (United States)

Author keywords

diffusion reaction model; EM; joint segmentation registration

Indexed keywords

BRAIN SCAN; DEFORMABLE REGISTRATION; DIFFUSION-REACTION MODEL; EM; EXPECTATION-MAXIMIZATION ALGORITHMS; GROUND TRUTH; GROWTH MODELS; JOINT SEGMENTATION; JOINT SEGMENTATION-REGISTRATION; MANUAL SEGMENTATION; POSTERIOR PROBABILITY; TUMOR GROWTH MODELS;

ALGORITHMS; DEFORMATION; IMAGE MATCHING; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MEDICAL IMAGING; PATIENT TREATMENT; TUMORS;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; BRAIN MAPPING; BRAIN TUMOR; GLIOMA; HUMAN; IMAGE PROCESSING; METHODOLOGY; NEOPLASM; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; BRAIN; BRAIN MAPPING; BRAIN NEOPLASMS; GLIOMA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; PROBABILITY;

EID: 80053532781     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23629-7_65     Document Type: Conference Paper

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