Detection of Colorectal Polyps in Colonoscopy Videos

Uses

  • 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.

Specifications

  • The proposed work is inspired from the AlexNet Model of CNN and called as containing 6 layers in the first approach, a layer removed in the second approach and then with a layer added.
  • All three were added from 50 epochs having batch size of 64, drop-out rate of 0.5, number of classes-2 and learning rate of 1e-4.

Applications

 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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