Adaptive energy selective active contour with shape priors for nuclear segmentation and gleason grading of prostate cancer

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

Volumn 6891 LNCS, Issue PART 1, 2011, Pages 661-669

  Ali, Sahirzeeshan ^a   Veltri, Robert ^b   Epstein, Jonathan I ^b   Christudass, Christhunesa ^b   Madabhushi, Anant ^a  

^a RUTGERS UNIVERSITY   (United States)

^b JOHNS HOPKINS HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOUR MODEL; ACTIVE CONTOURS; CLASSIFICATION ACCURACY; COMPUTATIONAL EXPENSE; COMPUTATIONAL OVERHEADS; COMPUTATIONAL TIME; DETECTION SCHEME; GLEASON GRADING; HISTOPATHOLOGICAL IMAGES; MORPHOLOGICAL FEATURES; MULTI-LEVEL; MULTIPLE OBJECTS; PROSTATE CANCERS; REGION-BASED; SHAPE BASED; SHAPE PRIORS; VARIATIONAL FORMULATION;

DISEASES; IMAGE SEGMENTATION; TISSUE;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CELL NUCLEUS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; HUMAN; IMAGE ENHANCEMENT; MALE; METABOLISM; METHODOLOGY; MICROARRAY ANALYSIS; PATHOLOGY; PROSTATE TUMOR; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL NUCLEUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; MICROARRAY ANALYSIS; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 82255185810     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23623-5_83     Document Type: Conference Paper

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