Bayesian registration via local image regions: Information, selection and marginalization

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

Volumn 5636 LNCS, Issue , 2009, Pages 435-446

  Toews, Matthew ^a   Wells III, William M ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APRIORI; BAYESIAN; GLOBAL REGISTRATION; IMAGE INTENSITIES; IMAGE LOCATIONS; IMAGE REGIONS; IMAGE-GUIDED; MARGINALIZATION; MUTUAL INFORMATIONS; NOVEL TECHNIQUES; SELECTION TECHNIQUES; SIMILARITY MEASURE; SPATIAL LOCATION;

BAYESIAN NETWORKS; DATA PROCESSING; MEDICAL IMAGING; RANDOM PROCESSES; RANDOM VARIABLES; ULTRASONIC APPLICATIONS;

ULTRASONIC IMAGING;

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

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

EID: 70349318367     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02498-6_36     Document Type: Conference Paper

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