Spatially adaptive log-euclidean polyaffine registration based on sparse matches

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 590-597

  Taquet, Maxime ^a,b   Macq, Benoît ^a   Warfield, Simon K ^b  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Log Euclidean; Polyaffine; Registration; Structure Tensor

Indexed keywords

ANATOMICAL STRUCTURES; BRAIN MRI; EXPECTATION MAXIMIZATION; HEALTHY SUBJECTS; ITERATIVE CLOSEST POINTS; LARGE STRUCTURES; LOG-EUCLIDEAN; MATCHING POINTS; MATHEMATICAL FRAMEWORKS; MULTIPLE SCLEROSIS; POLYAFFINE; REGISTRATION; SPATIALLY ADAPTIVE; STRUCTURE TENSOR;

DEFORMATION; MEDICAL COMPUTING;

IMAGE MATCHING;

ALGORITHM; ARTICLE; BRAIN; BRAIN MAPPING; DIAGNOSTIC IMAGING; HUMAN; IMAGE PROCESSING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BRAIN; BRAIN MAPPING; DATA INTERPRETATION, STATISTICAL; DIAGNOSTIC IMAGING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS;

EID: 80053486107     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23629-7_72     Document Type: Conference Paper

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