Automatic robust medical image registration using a new democratic vector optimization approach with multiple measures

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 590-597

  Wacker, Matthias ^a,b   Deinzer, Frank ^b,c  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b SIEMENS AG   (Germany)

^c UNIVERSITY OF APPLIED SCIENCES WÜRZBURG SCHWEINFURT   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; MEDICAL COMPUTING; MEDICAL IMAGING; MULTIOBJECTIVE OPTIMIZATION;

2-D-3-D REGISTRATION; CONTEXT INFORMATION; ITERATION PROCESS; LOCAL OPTIMIZATION STRATEGIES; NEW APPROACHES; NONCONVEX FUNCTIONS; SIMILARITY MEASURE; VECTOR OPTIMIZATIONS;

IMAGE REGISTRATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; EVALUATION; HUMAN; IMAGE QUALITY; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84883843903     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_73     Document Type: Conference Paper

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