Surface/volume-based articulated 3D spine inference through markov random fields

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

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 92-99

  Kadoury, Samuel ^a   Paragios, Nikos ^b  

^a Ecole Centrale de Paris   (France)

^b INRIA SACLAY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

3D RECONSTRUCTION; CT DATA; DEGREES OF FREEDOM; IMAGE GUIDANCES; IMAGE-BASED; INTRA-OPERATIVE; MARKOV RANDOM FIELDS; MODEL PARAMETERS; MULTI-MODAL; PAIRWISE CONSTRAINTS; SPINAL SURGERY; TRANSLATION PARAMETERS;

COMPUTERIZED TOMOGRAPHY; IMAGE FUSION; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; LINEARIZATION; MEDICAL COMPUTING; OPTIMIZATION; SURGERY;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE QUALITY; METHODOLOGY; PROBABILITY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SPINE; THREE DIMENSIONAL IMAGING;

ALGORITHMS; HUMANS; IMAGING, THREE-DIMENSIONAL; MARKOV CHAINS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPINE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84883841888     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_12     Document Type: Conference Paper

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