--- language: - en license: other tags: - medical - ophthalmology - fundus-image - image-classification - image-segmentation - pathologic-myopia - multi-task - optic-disc - lesion-segmentation task_categories: - image-classification - image-segmentation - object-detection task_ids: - multi-class-image-classification - semantic-segmentation pretty_name: PALM (Pathologic Myopia) Fundus Image Dataset size_categories: - 1K Merged Dataset Samples

Image: Dataset Samples.

--- ## ๐Ÿ“˜ Overview **PALM (Pathologic Myopia)** is a publicly available fundus image dataset developed for detecting **pathologic myopia (PM)** and analyzing associated retinal lesions and anatomical structures. It was released for the **Pathologic Myopia Challenge (PALM)**, hosted by the **Chinese Academy of Sciences** and **Sun Yat-sen University**, and published on **IEEE DataPort**. The dataset provides both **classification** and **segmentation** tasks, making it valuable for multi-task ophthalmic AI research. ๐Ÿ”— **Official Sources:** - [PALM Challenge (IEEE DataPort)](https://ieee-dataport.org/documents/palm-pathologic-myopia-challenge) - [PALM Dataset Publication (PMC)](https://pmc.ncbi.nlm.nih.gov/articles/PMC10799845/) - [ResearchGate Dataset Overview](https://www.researchgate.net/figure/Folder-organization-of-our-PALM-dataset_fig6_377564136) --- ## ๐Ÿ“Š Dataset Summary | Feature | Description | |----------|-------------| | **Images** | 1,200 color fundus photographs | | **Labels** | Binary โ€” *Pathologic Myopia (PM)* or *Non-PM* | | **Annotations** | Optic disc boundary, fovea location, and lesion masks (atrophy, detachment) | | **Resolution** | Varies (45ยฐ field-of-view fundus images) | | **Format** | JPEG | | **Tasks** | Classification, Segmentation | | **Source Institutions** | Multiple ophthalmic centers in China | | **License** | Free for research and educational use | | **Released** | 2019 (PALM Challenge) | --- ## ๐Ÿ“ Folder Structure ```python PALM/ โ”œโ”€โ”€ images/ โ”‚ โ”œโ”€โ”€ train/ โ”‚ โ”œโ”€โ”€ validation/ โ”‚ โ””โ”€โ”€ test/ โ”œโ”€โ”€ annotations/ โ”‚ โ”œโ”€โ”€ optic_disc_masks/ โ”‚ โ”œโ”€โ”€ lesion_masks/ โ”‚ โ””โ”€โ”€ fovea_locations.csv โ”œโ”€โ”€ labels.csv โ””โ”€โ”€ README.md ``` --- ## ๐Ÿฉธ Labels and Annotations - **Classification Label:** - `1` = Pathologic Myopia (PM) - `0` = Non-Pathologic (Normal) - **Segmentation Annotations:** - Optic disc boundaries - Fovea coordinates - Lesion masks for: - Patchy atrophy - Retinal detachment - Peripapillary atrophy --- ## ๐Ÿง  Research Applications PALM is designed for: - **Pathologic Myopia detection** from fundus images - **Segmentation** of optic disc, fovea, and lesion regions - **Multi-task learning** combining classification and segmentation - **Explainable AI** studies on high-myopia pathology --- ## โš™๏ธ Limitations - Limited image count (~1,200) - Variability in camera type and illumination - Binary labeling (PM vs Non-PM) does not cover all clinical myopia subtypes - Lesion annotations may need preprocessing for some segmentation frameworks --- ## ๐Ÿ“ฅ Access and Citation ### ๐Ÿ”— Access Dataset available via official IEEE DataPort page: ๐Ÿ‘‰ [https://ieee-dataport.org/documents/palm-pathologic-myopia-challenge](https://ieee-dataport.org/documents/palm-pathologic-myopia-challenge) ### ๐Ÿ“„ Citation If you use PALM, please cite: Fang H., Li F., Wu J., Fu H., Sun X., Orlando J. I., Bogunoviฤ‡ H., Zhang X., Xu Y. PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation. IEEE DataPort, 2019. --- ## ๐Ÿงพ License The PALM dataset is made available **for research and educational use only**. Redistribution or commercial use requires permission from the dataset authors.