Cervical Cancer Screening
To use deep learning for providing automated solutions for disease diagnosis due to its self-learning capability.
To propose a deep learning method for the detection of colorectal polyps from colonoscopy videos using CNN to enhance the accuracy and sensitivity of the existing methods.
- The proposed work is inspired from the ALexNet Model of CNN and called as the containing 6 layers in the first approach,a layer removed in second approach and then with a layer added.
- All three were executed for 50 epochs having batchsize of 64, dropout-rate of 0.5, number of classes-2 and learning rate of 1e-4.
The automated system can save the traditional manual and time consuming processes.
The proposed CAD system can be used for large scale screening of colorectal polyps at the medical institutes.
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