Automatic image analysis of histopathology specimens using concave vertex graph

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 833-841

  Yang, Lin ^a,c   Tuzel, Oncel ^b   Meer, Peter ^a   Foran, David J ^c  

^a RUTGERS UNIVERSITY   (United States)

^b RUTGERS UNIVERSITY   (United States)

^c RUTGERS CANCER INSTITUTE OF NEW JERSEY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE CONTOUR MODEL; AUTOMATIC IMAGE ANALYSIS; BLOOD CANCER; COMPUTATIONALLY EFFICIENT; DATA SETS; EARLY DETECTION; MORPHOLOGICAL CHARACTERISTIC; NOVEL ALGORITHM; OPTIMAL PATHS; ROBUST ESTIMATION; SEGMENTATION ALGORITHMS; TOUCHING CELLS; VERTEX GRAPHS;

ALGORITHMS; COMPUTER SCIENCE; GRAPH THEORY; IMAGE ANALYSIS; MEDICAL COMPUTING;

EDGE DETECTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; LEUKEMIA; LYMPHOMA; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; TUMOR CELL CULTURE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HISTOLOGICAL TECHNIQUES; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LEUKEMIA; LYMPHOMA; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TUMOR CELLS, CULTURED;

EID: 79551685885     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_99     Document Type: Conference Paper

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