Dense registration with deformation priors

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

Volumn 5636 LNCS, Issue , 2009, Pages 540-551

  Glocker, Ben ^a,b   Komodakis, Nikos ^c   Navab, Nassir ^b   Tziritas, Georgios ^c   Paragios, Nikos ^a,d  

^a ECOLE CENTRALE PARIS   (France)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF CRETE   (Greece)

^d INRIA SACLAY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER CENTERS; CLUSTERING TECHNIQUES; CONNECTED GRAPH; CONTROL POINT; DEFORMABLE IMAGE REGISTRATION; GLOBAL STRUCTURE; IMAGE CORRESPONDENCE; MARKOV RANDOM FIELDS; PRIOR KNOWLEDGE; RELATIVE DEFORMATION; SYNTHETIC AND REAL DATA; TASK-DRIVEN; TRAINING SETS;

DATA PROCESSING; GRAPH THEORY; HIDDEN MARKOV MODELS; IMAGE REGISTRATION; LINEARIZATION; MEDICAL IMAGING;

DEFORMATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 70349317175     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02498-6_45     Document Type: Conference Paper

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