European Journal of Molecular & Clinical Medicine

Abstract

Deep learning have earned major popularity in the today world by captured best results in medical analysis field. This research explained the stages of Oral squamous cell carcinoma using the convolution neural network model in deep Learning. Whenever the pathologist examine the photomicrograph image they faced a lot of difficulties to process and finding the stages of oral squamous cell carcinoma into poorly differentiated, medium differentiated and low differentiated. To avoid the difficulties of stages differentiation, the convolution neural network model has been implemented in this research. In the methodology part of Deep learning basically needs large number of data to perform good result so in this work image augmentation was performed to improve the better performance level of deep learning. Finally segmentation has been implemented and the segmented values are given to the convolution neural networks and it gives better accuracy of 85% when compared with all other deep learning techniques