Toward automatic mitotic cell detection and segmentation in multispectral histopathological images

IEEE Journal of Biomedical and Health Informatics

Volumn 18, Issue 2, 2014, Pages 594-605

  Lu, Cheng ^a   Mandal, Mrinal ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Histopathological image analysis; image segmentation; object detection; pattern recognition

Indexed keywords

BAYESIAN NETWORKS; CELLS; CYTOLOGY; DISCRIMINANT ANALYSIS; GRADING; IMAGE ANALYSIS; OBJECT DETECTION; PATTERN RECOGNITION;

DETECTION PERFORMANCE; HISTOPATHOLOGICAL IMAGE ANALYSIS; HISTOPATHOLOGICAL IMAGES; IMBALANCED CLASSIFICATION; LINEAR DISCRIMINANT ANALYSIS; MULTISPECTRAL IMAGES; SEGMENTATION PERFORMANCE; SURROUNDING REGIONS;

IMAGE SEGMENTATION;

ARTICLE; AUTOMATED PATTERN RECOGNITION; BREAST TUMOR; CANCER GRADING; CELL NUCLEUS; CYTOCHEMISTRY; DISCRIMINANT ANALYSIS; FEMALE; HUMAN; IMAGE PROCESSING; METHODOLOGY; MITOSIS; SENSITIVITY AND SPECIFICITY; ULTRASTRUCTURE;

BREAST NEOPLASMS; CELL NUCLEUS; DISCRIMINANT ANALYSIS; FEMALE; HISTOCYTOCHEMISTRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MITOSIS; NEOPLASM GRADING; PATTERN RECOGNITION, AUTOMATED; SENSITIVITY AND SPECIFICITY;

EID: 84896466493     PISSN: 21682194     EISSN: None     Source Type: Journal    
DOI: 10.1109/JBHI.2013.2277837     Document Type: Article

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