A novel graphical model approach to segmenting cell images

Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06

Volumn , Issue , 2006, Pages 482-489

  Chen, Shann Ching ^a   Zhao, Ting ^a   Gordon, Geoffrey J ^b   Murphy, Robert F ^a,b,c  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b Carnegie Mellon University   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOCOMMUNICATIONS; BIOINFORMATICS; CELLS; COMPUTATIONAL GEOMETRY; COPYING; CYTOLOGY; ESTIMATION; FLUORESCENCE MICROSCOPY; GRAPH THEORY; GRAPHIC METHODS; IMAGE ANALYSIS; IMAGE ENHANCEMENT; IMAGING TECHNIQUES; INFORMATION SCIENCE; INTELLIGENT CONTROL; MICROSCOPIC EXAMINATION; NUCLEIC ACIDS; ORGANIC ACIDS; PROBABILITY; RISK ASSESSMENT; YEAST;

APPROXIMATION APPROACH; AUTOMATED MICROSCOPY; BAYES NETWORKS; BOUNDARY INFORMATION; CELL BOUNDARIES; CELL IMAGING; COMPUTATIONAL BIOLOGY; COMPUTATIONAL INTELLIGENCE; CONVENTIONAL TECHNIQUES; DIFFERENTIAL INTERFERENCE CONTRAST; DNA PROBES; GRAPHICAL MODELLING; LABELED DATA; MULTI-CELL; NUCLEAR POSITIONS; PARALLEL IMAGING; REGIONS OF INTEREST; YEAST CELLS;

PIXELS;

EID: 50249090921     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIBCB.2006.330975     Document Type: Conference Paper

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