2D and 3D shape based segmentation using deformable models

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

Volumn 3750 LNCS, Issue , 2005, Pages 821-829

  El Baz, Ayman ^a   Yuksel, Seniha E ^a   Shi, Hongjian ^a   Farag, Aly A ^a   El Ghar, Mohamed A ^b   Eldiasty, Tarek ^b   Ghoneim, Mohamed A ^b  

^a University of Louisville   (United States)

^b MANSOURA UNIVERSITY   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

DEFORMABLE MODELS; LINEAR COMBINATION OF DISCRETE GAUSSIAN (LCDG); SHAPE BASED SEGMENTATION; VENTRICLE SEGMENTATION;

MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; MEDICAL APPLICATIONS; MEDICAL IMAGING; RADIOLOGY; THREE DIMENSIONAL; TWO DIMENSIONAL;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; ELASTICITY; EVALUATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; KIDNEY; METHODOLOGY; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER SIMULATION; ELASTICITY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; KIDNEY; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33744783989     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11566489_101     Document Type: Conference Paper

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