Modern medical image processing techniques work on histopathology images captured by a microscope, and then analyze them by using different algorithms and methods. Manual detection of a cancer cell is a tiresome task and involves human error, and hence computer-aided mechanisms are applied to obtain better results as compared with manual pathological detection systems.
In this project, we perform exploratory analysis on the data and try out different models to give the best results.
We train a Convolutional Neural Network on dataset achieving an accuracy of 94.64%. Architecture of the same:
