DeepPap: Deep convolutional networks for cervical cell classification

IEEE Journal of Biomedical and Health Informatics

Volumn 21, Issue 6, 2017, Pages 1633-1643

  Zhang, Ling ^a   Lu, Le ^a   Nogues, Isabella ^a   Summers, Ronald M ^a   Liu, Shaoxiong ^b   Yao, Jianhua ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b Ministry of Education Nanshan District   (China)

Author keywords

Cell classification; Cervical cytology; deep learning; neural networks; Pap smear

Indexed keywords

CELLS; CLASSIFICATION (OF INFORMATION); CONVOLUTION; CYTOLOGY; DEEP LEARNING; DEEP NEURAL NETWORKS; IMAGE SEGMENTATION; NEURAL NETWORKS; TEXTURES;

AREA UNDER THE CURVES; CANCER DETECTION; CELL CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; CONVOLUTIONAL NETWORKS; CROSS VALIDATION; PAP SMEAR;

CONVOLUTIONAL NEURAL NETWORKS;

ACCURACY; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CERVICAL CELL LINE; DIAGNOSTIC TEST ACCURACY STUDY; HUMAN; IMAGE SEGMENTATION; LEARNING; PAPANICOLAOU TEST; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; TRAINING; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; FEMALE; MACHINE LEARNING; PROCEDURES; UTERINE CERVIX; VAGINA SMEAR;

CERVIX UTERI; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER); PAPANICOLAOU TEST; VAGINAL SMEARS;

EID: 85035807487     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2017.2705583     Document Type: Article

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