This is a Oral cancer Detection Web-App, Build using Flask, Tensorflow, Keras and CV2. The Model is trained on preprocessed Histopathalogical Images of Oral Cancer with. Custom XceptionNet model is trained which detect the presence of cancer with 98% accuracy.
Oral cancer is a serious public health issue worldwide, and
early detection is crucial to improve survival rates and reduce
the negative impact on patient's lives. While histopathological
examination is the standard method for diagnosis, it can be
time-consuming and prone to errors. However, recent advancements in deep learning, particularly convolutional neural neworks (CNNs), have shown promise in accurately diagnosing
and analyzing biomedical images, making them a potential
tool for early classification of cancer using histopathological
image.
Updategadh@gmail.com