Generative Adversarial Networks for Automatic Polyp Segmentation
2020-12-12Code Available0· sign in to hype
Awadelrahman M. A. Ali Ahmed
Code Available — Be the first to reproduce this paper.
ReproduceCode
Abstract
This paper aims to contribute in bench-marking the automatic polyp segmentation problem using generative adversarial networks framework. Perceiving the problem as an image-to-image translation task, conditional generative adversarial networks are utilized to generate masks conditioned by the images as inputs. Both generator and discriminator are convolution neural networks based. The model achieved 0.4382 on Jaccard index and 0.611 as F2 score.