Abstract:
"Oral cancer is one of the most dangerous disease in world. We can see raising number
of patients in Sri Lanka. Tobacco and smoking are main factors oral cancer. This oral
cancer affects the oral cavity in the mouth. Test for the oral cancer diagnose is very
painful and costly. Early diagnose of oral cancer will increase the survival rate.
Computer vision or image processing will help to do the early diagnose of oral cancer
without pain.
This application will help to detect the oral cancer using image processing. Patient or
physician can test their oral cavity with an image without pain. This application will
use machine learning machines to predict the Oral cancer. This application will detect
that lesion or patch is a cancerous. If lesion or patch is cancerous it will categorise that
lesion or patch. This application mixed of pre-processing, libraries, algorithms and
validations. This application two main machine learning models which trained and
evaluated models.
This application is develop with Python language. This application is well designed
and structured. This application will use RGB image to detect the Oral Cancer. This
application is developed with 3 main libraries, 2 machine learning model and 4
algorithms. It is easy to use and test the lesion."
