A coupled global registration and segmentation framework with application to magnetic resonance prostate imagery

IEEE Transactions on Medical Imaging

Volumn 29, Issue 10, 2010, Pages 1781-1794

  Gao, Yi ^a   Sandhu, Romeil ^a   Fichtinger, Gabor ^b   Tannenbaum, Allen Robert ^a,c  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b QUEEN S UNIVERSITY   (Canada)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Image registration; Particle filtering; Prostate segmentation; Shape based segmentation

Indexed keywords

CLINICAL DATA; COST FUNCTIONALS; GLOBAL ASPECTS; GLOBAL REGISTRATION; LOCAL IMAGE STATISTICS; MEDICAL IMAGE ANALYSIS; PARTICLE FILTERING; POINT CLOUD; PROSTATE SEGMENTATION; REGISTRATION PROBLEMS; SHAPE BASED; SHAPE PRIORS; SURGICAL PLANNING; TRAINING SETS;

IMAGE ANALYSIS; IMAGE REGISTRATION; MAGNETIC RESONANCE; MEDICAL IMAGING; NONLINEAR FILTERING;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; MALE; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROSTATE; PROSTATE TUMOR; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; PATTERN RECOGNITION, AUTOMATED; PROSTATE; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 77957563337     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2010.2052065     Document Type: Article

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