mlsanityData to 7 Oct 2026

Attention Guided Network for Retinal Image Segmentation

arXiv 1907.12930 ↗First posted 25 Jul 2019eess.IV cs.CVcited by 31

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Abstract (arXiv)

Learning structural information is critical for producing an ideal result in retinal image segmentation. Recently, convolutional neural networks have shown a powerful ability to extract effective representations. However, convolutional and pooling operations filter out some useful structural information. In this paper, we propose an Attention Guided Network (AG-Net) to preserve the structural information and guide the expanding operation. In our AG-Net, the guided filter is exploited as a structure sensitive expanding path to transfer structural information from previous feature maps, and an attention block is introduced to exclude the noise and reduce the negative influence of background further. The extensive experiments on two retinal image segmentation tasks (i.e., blood vessel segmentation, optic disc and cup segmentation) demonstrate the effectiveness of our proposed method.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jul 2019.

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Citing papers per year: 2021: 5; 2022: 10; 2023: 9; 2024: 3; 2025: 4.

31 papers.

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  1. 2021Applications of Deep Learning in Fundus Images: A Reviewcited by 59
  2. 2022ImageCAS: A Large-Scale Dataset and Benchmark for Coronary Artery Segmentation based on Computed Tomography Angiography Imagescited by 54
  3. 2022AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Imagescited by 43
  4. 2021Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Networkcited by 42
  5. 2022RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imagingcited by 12
  6. 2023DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequencescited by 10
  7. 20213D AGSE-VNet: An Automatic Brain Tumor MRI Data Segmentation Frameworkcited by 9
  8. 2023Attention Mechanisms in Medical Image Segmentation: A Surveycited by 9
  9. 2022Learning self-calibrated optic disc and cup segmentation from multi-rater annotationscited by 8
  10. 2023Generative appearance replay for continual unsupervised domain adaptationcited by 8
  11. 2024DSCA: A Digital Subtraction Angiography Sequence Dataset and Spatio-Temporal Model for Cerebral Artery Segmentationcited by 8
  12. 2023Bridging Synthetic and Real Images: a Transferable and Multiple Consistency aided Fundus Image Enhancement Frameworkcited by 5
19 more
  1. 2023Denoising Diffusion Probabilistic Model for Retinal Image Generation and Segmentationcited by 4
  2. 2024TESL-Net: A Transformer-Enhanced CNN for Accurate Skin Lesion Segmentationcited by 4
  3. 2022Retinal Vessel Segmentation with Pixel-wise Adaptive Filterscited by 3
  4. 2022Opinions Vary? Diagnosis First!cited by 3
  5. 2022Calibrate the inter-observer segmentation uncertainty via diagnosis-first principlecited by 3
  6. 2025Full-scale Representation Guided Network for Retinal Vessel Segmentationcited by 3
  7. 2025MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstructioncited by 3
  8. 2022SPNet: A novel deep neural network for retinal vessel segmentation based on shared decoder and pyramid-like losscited by 2
  9. 2022Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raterscited by 2
  10. 2021Attention W-Net: Improved Skip Connections for better Representationscited by 1
  11. 2023GAEI-UNet: Global Attention and Elastic Interaction U-Net for Vessel Image Segmentationcited by 1
  12. 2023Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentationcited by 1
  13. 2025SA-UNetv2: Rethinking Spatial Attention U-Net for Retinal Vessel Segmentationcited by 1
  14. 2021Quantifying Topology In Pancreatic Tubular Networks From Live Imaging 3D Microscopycited by 0
  15. 2022Exploring the Effects of Data Augmentation for Drivable Area Segmentationcited by 0
  16. 2023Overview of Deep Learning Methods for Retinal Vessel Segmentationcited by 0
  17. 2023BAAF: A benchmark attention adaptive framework for medical ultrasound image segmentation taskscited by 0
  18. 2024Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structurescited by 0
  19. 2025SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-Tuningcited by 0