A framework for diagnosing cervical cancer disease based on feedforward MLP neural network and ThinPrep histopathological cell image features

Neural Computing and Applications

Volumn 24, Issue 1, 2014, Pages 221-232

  Sokouti, Babak ^a   Haghipour, Siamak ^a   Tabrizi, Ali Dastranj ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b TABRIZ UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

Cell type; Cervical cancer; Classifier; Neural network; ThinPrep cell image

Indexed keywords

CELL IMAGES; CELL TYPES; CERVICAL CANCERS; CLASSIFICATION RATES; IMAGE PREPROCESSING; IMAGE PROCESSING ALGORITHM; MLP NEURAL NETWORKS; SENSITIVITY AND SPECIFICITY;

CELLS; CLASSIFIERS; CYTOLOGY; DAMAGE DETECTION; DIAGNOSIS; IMAGE CLASSIFICATION; NEURAL NETWORKS;

IMAGE PROCESSING;

EID: 84891882107     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-012-1220-y     Document Type: Article

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