Unsupervised segmentation of overlapped nuclei using bayesian classification

IEEE Transactions on Biomedical Engineering

Volumn 57, Issue 12, 2010, Pages 2825-2832

  Jung, Chanho ^a   Kim, Changick ^a   Chae, Seoung Wan ^b   Oh, Sukjoong ^b  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b Sungkyunkwan University School of Medicine   (South Korea)

Author keywords

Automatic cell segmentation; cluster validation; Gaussian mixture model; overlapped nuclei segmentation; unsupervised Bayesian classifier

Indexed keywords

BAYESIAN CLASSIFIER; CELL SEGMENTATION; CLUSTER VALIDATION; GAUSSIAN MIXTURE MODEL; NUCLEI SEGMENTATION;

BAYESIAN NETWORKS; BLIND SOURCE SEPARATION; CLASSIFIERS;

IMAGE SEGMENTATION;

ACCURACY; ALGORITHM; ARTICLE; AUTOMATION; BAYES THEOREM; CARCINOMA CELL; CELL ISOLATION; CELL NUCLEUS; HUMAN; HUMAN CELL; IMAGE ANALYSIS; MICROSCOPY; OVERLAPPED NUCLEUS SEGMENTATION; PERFORMANCE; PROCEDURES CONCERNING CELLS; UTERINE CERVIX; VALIDATION PROCESS;

ALGORITHMS; BAYES THEOREM; BREAST; BREAST NEOPLASMS; CARCINOMA, DUCTAL, BREAST; CELL NUCLEUS; CERVIX UTERI; CLUSTER ANALYSIS; DISCRIMINANT ANALYSIS; FEMALE; HISTOCYTOCHEMISTRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NORMAL DISTRIBUTION; REPRODUCIBILITY OF RESULTS;

EID: 78649247761     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2010.2060486     Document Type: Article

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