Abstract

‘Oral cytology’ is a potential strategy for early detection of oral cancers. The present work utilizes Deep Convolutional Neural Network (D-CNN) based classification model to detect normal and malignant cytological changes in Digital Holographic Microscopy (DHM) images of oral specimens.

© 2019 The Author(s)

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