Hybrid spline-based multimodal registration using local measures for joint entropy and mutual information

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

Volumn 5761 LNCS, Issue PART 1, 2009, Pages 607-615

  Biesdorf, Andreas ^a   Wörz, Stefan ^a   Kaiser, Hans Jürgen ^b   Stippich, Christoph ^c   Rohr, Karl ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b UNIVERSITY HOSPITAL RWTH AACHEN   (Germany)

^c UNIVERSITY HOSPITAL HEIDELBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN PHANTOMS; COMPUTATIONALLY EFFICIENT; ELASTIC REGISTRATION; HYBRID APPROACH; INTENSITY INFORMATION; JOINT ENTROPY; MULTIMODAL MEDICAL IMAGES; MULTIMODAL REGISTRATION; MUTUAL INFORMATIONS; SIMILARITY MEASURE; SYNTHETIC IMAGES;

INFORMATION THEORY; SPLINES;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; ENTROPY; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

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

EID: 79551681440     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_75     Document Type: Conference Paper

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