Active volume models with probabilistic object boundary prediction module

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 331-341

  Shen, Tian ^a   Zhu, Yaoyao ^a   Huang, Xiaolei ^a   Huang, Junzhou ^b   Metaxas, Dimitris ^b   Axel, Leon ^c  

^a Lehigh University   (United States)

^b Rutgers University School of Medicine   (United States)

^c NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOURS; ACTIVE VOLUMES; ADAPTIVE REGION; BASIC OPERATION; BAYESIAN DECISION RULE; DEFORMING OBJECTS; EXTERNAL FORCE; LEVEL SET METHOD; LEVEL SETS; MEDICAL IMAGES; NATURAL EXTENSION; OBJECT BOUNDARIES; OBJECT SEGMENTATION; REGION INFORMATION; SEGMENTATION RESULTS;

COMPUTER SCIENCE; IMAGE SEGMENTATION; LEVEL MEASUREMENT; MEDICAL IMAGING;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 58849091931     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_40     Document Type: Conference Paper

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