Polyp Localization In Colonscopy Videos using Single Shot Multibox Detector

Polyp-Classification-using-CNN

Towards One-stage Framework: Optimization of 3D FCNs for Polyp Detection in CT Colonography

A systematic study on the performance of different data augmentation methods for colon polyp detection.

Implementing polyp segmentation using the U-Net and CVC-612 dataset.

[MICCAI'22] Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.

Official repo of "EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)"

[TMI'22] A Source-free Domain Adaptive Polyp Detection Framework with Style Diversification Flow

Kvasir-SEG: A Segmented Polyp Dataset

Official implementation of ColonSegNet: Real-Time Polyp Segmentation (Used in NVIDIA Clara Holoscan App for Polyp Segmentation)

A multi-centre polyp detection and segmentation dataset for generalisability assessment https://www.nature.com/articles/s41597-023-01981-y

This research will show an innovative method useful in the segmentation of polyps during the screening phases of colonoscopies. To do this we have adopted a new approach which consists in merging the hybrid semantic network (HSNet) architecture model with the Reagion-wise(RW) as a loss function for the backpropagation process.