medical-3

Optic Cup Segmentation

3260 papers • 126 benchmarks • 313 datasets

Optic cup segmentation, concentric with optic disc, useful for glaucoma management (ophthalmology)

(Image credit: Papersgraph)

Benchmarks

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REFUGE Challenge

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REFUGE Challenge

SMDG

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Most implemented papers

G1020: A Benchmark Retinal Fundus Image Dataset for Computer-Aided Glaucoma Detection

A. Dengel, Sheraz Ahmed, Muhammad Naseer Bajwa, Gurbinder Singh, Wolfgang Neumeier, M. I. Malik•Wed May 27 2020

This database consists of 1020 high resolution colour fundus images and provides ground truth annotations for glaucoma diagnosis, optic disc and optic cup segmentation, vertical cup-to-disc ratio, size of neuroretinal rim in inferior, superior, nasal and temporal quadrants, and bounding box location for optic disc.

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MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model

Yu Zhang, Junde Wu, Huihui Fang, Yanwu Xu, Yehui Yang•Mon Oct 31 2022

The experimental results show that MedSegDiff outperforms state-of-the-art (SOTA) methods with considerable performance gap, indicating the generalization and effectiveness of the proposed model.

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Medical Image Segmentation using Squeeze-and-Expansion Transformers

Xiuchao Sui, Xinxing Xu, Shaohua Li, Xiangde Luo, Yong Liu, R. Goh•Wed May 19 2021

Segtran is an alternative segmentation framework based on transformers, which has unlimited effective receptive fields even at high feature resolutions, and a new positional encoding scheme for transformers is proposed, imposing a continuity inductive bias for images.

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