Computing maximum association graph in microscopic nucleus images

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

Volumn 6362 LNCS, Issue PART 2, 2010, Pages 530-537

  Stojkovic, Branislav ^a   Zhu, Yongding ^a   Xu, Jinhui ^a   Fritz, Andrew ^b   Zeitz, Michael J ^c   Vecerova, Jaromira ^b   Berezney, Ronald ^c  

^a State University of New York   (United States)

^b UNIVERSITY AT BUFFALO   (United States)

^c STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION GRAPH; ASSOCIATION PATTERNS; CELL BIOLOGY; CELL NUCLEUS; CELL PROCESS; INTEGER LINEAR PROGRAMMING FORMULATION; LARGE DATASETS; NOVEL TECHNIQUES; OPTIMAL APPROXIMATION; OPTIMAL SOLUTIONS; TWO STAGE;

CHROMOSOMES; CYTOLOGY; GENE EXPRESSION; GENE EXPRESSION REGULATION; INTEGER PROGRAMMING; MEDICAL COMPUTING; OPTIMIZATION;

MEDICAL IMAGING;

ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHROMOSOME; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MICROSCOPY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; ULTRASTRUCTURE;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; CHROMOSOMES; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 78349274388     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15745-5_65     Document Type: Conference Paper

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