mlsanityData to 14 Oct 2026

PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation

arXiv 2305.07816 ↗First posted 13 May 2023eess.IV cs.CVcited by 11

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Abstract (arXiv)

Pathologic myopia (PM) is a common blinding retinal degeneration suffered by highly myopic population. Early screening of this condition can reduce the damage caused by the associated fundus lesions and therefore prevent vision loss. Automated diagnostic tools based on artificial intelligence methods can benefit this process by aiding clinicians to identify disease signs or to screen mass populations using color fundus photographs as inputs. This paper provides insights about PALM, our open fundus imaging dataset for pathological myopia recognition and anatomical structure annotation. Our databases comprises 1200 images with associated labels for the pathologic myopia category and manual annotations of the optic disc, the position of the fovea and delineations of lesions such as patchy retinal atrophy (including peripapillary atrophy) and retinal detachment. In addition, this paper elaborates on other details such as the labeling process used to construct the database, the quality and characteristics of the samples and provides other relevant usage notes.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 9 of its 33 references that are in the map. First posted on arXiv 13 May 2023.

Builds on

9 of 33 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 228
  4. 2021Applications of Deep Learning in Fundus Images: A Reviewcited by 59
  5. 2019Evaluation of Retinal Image Quality Assessment Networks in Different Color-spacescited by 57
  6. 2022ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Imagescited by 25
  7. 2022Dataset and Evaluation algorithm design for GOALS Challengecited by 13
  8. 2018Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis -- A Reviewcited by 11
  9. 2020Pathological myopia classification with simultaneous lesion segmentation using deep learningcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 5; 2026: 1.

11 papers.

  1. 2024OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLMcited by 184
  2. 2024A Survey of Medical Vision-and-Language Applications and Their Techniquescited by 11
  3. 2024SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imagingcited by 5
  4. 2024VascX Models: Model Ensembles for Retinal Vascular Analysis from Color Fundus Imagescited by 4
  5. 2024F3OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristicscited by 4
  6. 2025Predicting Diabetic Macular Edema Treatment Responses Using OCT: Dataset and Methods of APTOS Competitioncited by 3
  7. 2025Boosting Medical Visual Understanding From Multi-Granular Language Learningcited by 2
  8. 2025PSScreen: Partially Supervised Multiple Retinal Disease Screeningcited by 1
  9. 2025Native Intelligence Emerges from Large-Scale Clinical Practice: A Retinal Foundation Model with Deployment Efficiencycited by 1
  10. 2025PSScreen V2: Partially Supervised Multiple Retinal Disease Screeningcited by 0
  11. 2026EyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Groundingcited by 0