Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: A comprehensive review

IEEE Reviews in Biomedical Engineering

Volumn 9, Issue , 2016, Pages 234-263

  Xing, Fuyong ^a   Yang, Lin ^a  

^a J Crayton Pruitt Family Department of Biomedical Engineering   (United States)

Author keywords

Cell; detection; digital pathology; histopathology; microscopy images; nucleus; segmentation

Indexed keywords

CELLS; COMPUTER AIDED DIAGNOSIS; ERROR DETECTION; PATHOLOGY;

COMPUTER AIDED DIAGNOSIS SYSTEMS; DIFFERENTIAL INTERFERENCE CONTRAST; DIGITAL PATHOLOGIES; HISTOPATHOLOGY; MICROSCOPY IMAGE ANALYSIS; MICROSCOPY IMAGES; MORPHOLOGICAL INFORMATION; NUCLEUS;

IMAGE SEGMENTATION;

BLADDER CANCER; BREAST CANCER; BRIGHT FIELD MICROSCOPY; CANCER DIAGNOSIS; CELL SHAPE; CELL STRUCTURE; CLASSIFIER; COMPUTER ASSISTED DIAGNOSIS; FLOODING; FLUORESCENCE MICROSCOPY; FOLLICULAR LYMPHOMA; HUMAN; IMAGE ANALYSIS; IMAGE SEGMENTATION; KERNEL METHOD; MICROSCOPY; NUCLEUS CELL DETECTION; PATHOLOGY; QUANTITATIVE ANALYSIS; RADIOLOGICAL PARAMETERS; RANDOM FOREST; REPRODUCIBILITY; REVIEW; RNA INTERFERENCE; SUPPORT VECTOR MACHINE; SURVIVAL ANALYSIS; WATERSHED; CELL NUCLEUS; PROCEDURES;

CELL NUCLEUS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY;

EID: 84989933991     PISSN: 19373333     EISSN: 19411189     Source Type: Journal    
DOI: 10.1109/RBME.2016.2515127     Document Type: Review

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