An optimal transportation approach for nuclear structure-based pathology

IEEE Transactions on Medical Imaging

Volumn 30, Issue 3, 2011, Pages 621-631

  Wang, Wei ^a   Ozolek, John A ^b   Slepčev, Dejan ^c   Lee, Ann B ^c   Chen, Cheng ^a   Rohde, Gustavo K ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b CHILDREN S HOSPITAL OF PITTSBURGH   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Cancer detection; classification; nuclear structure; optimal transportation; pathology

Indexed keywords

AUTOMATIC DETERMINATION; BIOLOGICAL INFORMATION; CANCER DETECTION; CLASSIFICATION; CLASSIFICATION ACCURACY; FISHER DISCRIMINANT ANALYSIS; IMAGE DATA; MALIGNANT TISSUES; MICROSCOPY IMAGES; MULTIDIMENSIONAL SCALING TECHNIQUES; NUCLEAR MORPHOLOGY; NUCLEAR STRUCTURE; NUMERICAL FEATURES; OPTIMAL TRANSPORTATION; QUANTITATIVE INFORMATION; SURGICAL PATHOLOGY; THYROID CANCERS; TRANSPORTATION METRIC;

DISCRIMINANT ANALYSIS; DISEASES; FISHER INFORMATION MATRIX; LIVER; MORPHOLOGY; NUCLEAR PHYSICS; PATHOLOGY; SURGERY;

STRUCTURAL OPTIMIZATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CELL NUCLEUS; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; LIVER TUMOR; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THYROID TUMOR;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL NUCLEUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LIVER NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; THYROID NEOPLASMS;

EID: 79952119640     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2010.2089693     Document Type: Article

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