Combining fully convolutional networks and graph-based approach for automated segmentation of cervical cell nuclei

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2017, Pages 406-409

  Zhang, Ling ^a   Sonka, Milan ^b   Lu, Le ^a   Summers, Ronald M ^a   Yao, Jianhua ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b University of Iowa   (United States)

Author keywords

Deep learning; FCN; Graph based segmentation; Pap smear

Indexed keywords

AUTOMATION; CONVOLUTION; COST FUNCTIONS; CYTOLOGY; DEEP LEARNING; GRAPHIC METHODS; MEDICAL IMAGING;

AUTOMATED SEGMENTATION; CERVICAL CANCERS; CERVICAL CELLS; CONVOLUTIONAL NETWORKS; GRAPH-BASED SEGMENTATION; HIGH-LEVEL FEATURES; PAP SMEAR; SIMILARITY INDICES;

DYNAMIC PROGRAMMING;

EID: 85023189143     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2017.7950548     Document Type: Conference Paper

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