Fast and robust clinical triple-region image segmentation using one level set function

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

Volumn 4191 LNCS - II, Issue , 2006, Pages 766-773

  Li, Shuo ^a,b   Fevens, Thomas ^b   Krzyzak, Adam ^b   Jin, Chao ^b   Li, Song ^c  

^a GE HEALTHCARE   (Canada)

^b Dept of Electrical and Computer Engineering   (Canada)

^c ANHUI MEDICAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DIAGNOSIS; FUNCTION EVALUATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; PROBLEM SOLVING; SET THEORY; X RAY ANALYSIS;

AUTOMATIC COMPUTER AIDED DIAGNOSIS; CLINICAL ACCELERATION; CLINICAL SEGMENTATION; LEVEL SET FUNCTIONS;

IMAGE SEGMENTATION;

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

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

EID: 33750253673     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866763_94     Document Type: Conference Paper

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