Nonrigid registration of dynamic renal MR images using a saliency based MRF model

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 771-779

  Mahapatra, Dwarikanath ^a   Sun, Ying ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE REGISTRATION; CONTRAST AGENT; CONTRAST-ENHANCED IMAGES; CONTRAST-ENHANCED MR; DEFORMATION FIELD; DEGREE OF SIMILARITY; EDGE INFORMATION; ELASTIC MOTIONS; EXPONENTIAL FUNCTIONS; INTENSITY INFORMATION; MARKOV RANDOM FIELDS; MR IMAGES; NONRIGID REGISTRATION; ORIENTATION HISTOGRAMS; PATIENT DATASETS; PIXEL INTENSITIES;

COMPUTER SCIENCE; HIDDEN MARKOV MODELS; MEDICAL COMPUTING; MEDICAL IMAGING;

EDGE DETECTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; KIDNEY; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PROBABILITY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; KIDNEY; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; MODELS, ANATOMIC; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 83455195913     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_92     Document Type: Conference Paper

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