Oral cancer is one of the most common malignant tumors. There are 354,864 new cases and 177,384 death per year globally according to Globocan 2018 report. Most of the cases are in low- and middle-income countries that lack trained specialists and health services, of which India accounts for approximately one-third of the new cases and two-fifth deaths. Point-of-care oral screening tool to enable early diagnosis is urgently needed. We developed a dual-mode intraoral oral cancer screening platform and an automatic classification algorithm for oral dysplasia and malignancy images using deep learning.
Oral cancer is a rising health issue in many low and middle income countries (LMIC). Proposed is an implementation of autofluorescence imaging (AFI) and white light imaging (WLI) on a smartphone platform providing inexpensive early detection of cancerous conditions in the oral cavity. Interchangeable modules allow both whole mouth imaging for an overview of the patients’ oral health and an intraoral imaging probe for localized information. Custom electronics synchronize image capture and external LED operation for the excitation of tissue fluorescence. A custom Android application captures images and an image processing algorithm provides likelihood estimates of cancerous conditions. Finally, all data can be uploaded to a cloud server where a convolutional neural network classifies the images and a remote specialist can provide diagnosis and triage instructions.
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