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Polyp Segmentation

The goal of the project is to develop a computer-aided detection and diagnosis system for automatic polyp segmentation and detection.

Papers

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Showing 1–10 of 10 papers

TitleStatusHype
Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 ModelCode2
KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp SegmentationCode1
TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution TestingCode1
Multi Kernel Positional Embedding ConvNeXt for Polyp SegmentationCode1
Medical Image Segmentation via Cascaded Attention DecodingCode1
TGANet: Text-guided attention for improved polyp segmentationCode1
BDG-Net: Boundary Distribution Guided Network for Accurate Polyp SegmentationCode1
ResUNet++: An Advanced Architecture for Medical Image SegmentationCode1
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise BinarizationCode0
Kvasir-SEG: A Segmented Polyp DatasetCode0
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