Data · dataset · 2026
OmniMedSeg-OCT
Listed in RADAR and RADAR4Memory — shown once because both records carry DOI 10.35097/7qp3vq1qc5bp18uj
Description
This dataset contains 5 converted OCT datasets, part of the OmniMedSeg superset. All datasets are converted to a standardized structure with binary masks for each segmentation target. ================================================================================ DATASET LICENSE AND CITATION SUMMARY ================================================================================ -------------------------------------------------------------------------------- QUICK REFERENCE: DATASETS AND LICENSES -------------------------------------------------------------------------------- AIDK: CC0 1.0 AMD_SD: CC0 1.0 INTRARETINAL_CYSTOID_FLUID: CC-BY-NC-SA 4.0 OCT_LESION: CC-BY 4.0 OIMHS: CC0 1.0 ================================================================================ DETAILED INFORMATION BY DATASET ================================================================================ [1] AIDK ---------------------------------------- License: CC0 1.0 Dataset link: springernature.figshare.com/articles/dataset/An_AS-OCT_image_dataset_for_deep_learning-enabled_segmentation_and_3D_reconstruction_for_keratitis/25952845?backTo=%2Fcollections%2FAIDK_An_AS-OCT_image_dataset_for_deep_learning-enabled_segmentation_and_3D_reconstruction_for_keratitis%2F7036994&file=46760137 Metadata file: OCT/AIDK/metadata.json Citation (bibtex): @article{Sun2024, author = "Yiming Sun and Nuliqiman Maimaiti and Peifang Xu and Jingxuan Cai and Pengjie Chen and Mingyu Xu and Juan Ye", title = "{An AS-OCT image dataset for deep learning-enabled segmentation and 3D reconstruction for keratitis}", year = "2024", month = "6", url = "springernature.figshare.com/articles/dataset/An_AS-OCT_image_dataset_for_deep_learning-enabled_segmentation_and_3D_reconstruction_for_keratitis/25952845", doi = "10.6084/m9.figshare.25952845.v1" } ---------------------------------------- [2] AMD_SD ---------------------------------------- License: CC0 1.0 Dataset link: springernature.figshare.com/articles/dataset/An_Optical_Coherence_Tomography_Image_Dataset_for_wet_AMD_Lesions_Segmentation/25513435?backTo=%2Fcollections%2FAMD-SD_An_Optical_Coherence_Tomography_Image_Dataset_for_wet_AMD_Lesions_Segmentation%2F7157554&file=48777037 Metadata file: OCT/AMD_SD/metadata.json Citation (bibtex): @article{Li2024, author = "Guodong Li and Yunwei Hu and Yundi Gao and Weihao Gao and Wenbin Luo and Zhongyi Yang and Fen Xiong and Zidan Chen and Yucai Lin and Xinjing Xia and Xiaolong Yin and Yan Deng and Lan Ma", title = "{An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation}", year = "2024", month = "9", url = "springernature.figshare.com/articles/dataset/An_Optical_Coherence_Tomography_Image_Dataset_for_wet_AMD_Lesions_Segmentation/25513435", doi = "10.6084/m9.figshare.25513435.v1" } ---------------------------------------- [3] INTRARETINAL_CYSTOID_FLUID ---------------------------------------- License: CC-BY-NC-SA 4.0 Dataset link: kaggle.com/datasets/zeeshanahmed13/intraretinal-cystoid-fluid Metadata file: OCT/INTRARETINAL_CYSTOID_FLUID/metadata.json Citation (bibtex): @article{ahmed2022deep, title={Deep learning based automated detection of intraretinal cystoid fluid}, author={Ahmed, Zeeshan and Panhwar, Shahbaz Qamar and Baqai, Attiya and Umrani, Fahim Aziz and Ahmed, Munawar and Khan, Arbaaz}, journal={International Journal of Imaging Systems and Technology}, volume={32}, number={3}, pages={902--917}, year={2022}, publisher={Wiley Online Library} } ---------------------------------------- [4] OCT_LESION ---------------------------------------- License: CC-BY 4.0 Source: 'license' field Dataset link: kaggle.com/datasets/zeeshanahmed13/intraretinal-cystoid-fluid Metadata file: OCT/OCT_LESION/metadata.json Citation (bibtex): @data{Yoo2020OCT, author = {Yoo, TaeKeun}, title = {Data for: Improved accuracy in OCT diagnosis of rare retinal disease using few-shot learning with generative adversarial networks}, year = 2020, version = {V2}, publisher = {Mendeley Data}, doi = {10.17632/btv6yrdbmv.2}, url = {doi.org/10.17632/btv6yrdbmv.2} } ---------------------------------------- [5] OIMHS ---------------------------------------- License: CC0 1.0 Dataset link: springernature.figshare.com/articles/dataset/OIMHS_dataset/23508453?file=42522673 Metadata file: OCT/OIMHS/metadata.json Citation (bibtex): @article{Shen2023, author = "Lijun Shen and Xin Ye and Shucheng He and Xiaxing Zhong and Yingjiao Shen and Shangchao Yang and Yiqi Chen and Xingru Huang", title = "{OIMHS dataset}", year = "2023", month = "10", url = "springernature.figshare.com/articles/dataset/OIMHS_dataset/23508453", doi = "10.6084/m9.figshare.23508453.v1" } ---------------------------------------- ================================================================================ IMPORTANT NOTES ================================================================================ - All datasets listed are publicly available - Full metadata is stored in each dataset's metadata.json file - For CC0-licensed datasets, attribution is appreciated but not required - For other licenses, please review the specific terms before use
Links
Where it is published
- DOI doi.org/10.35097/7qp3vq1qc5bp18uj ↗
DOI / persistent id · from radar service eu de
Catalogue records · 1
- OAI-PMH record radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=oai_dc&identifier… ↗
metadata API · from radar service eu de
Topics
Provenance · 2 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| RADAR | 10.35097/7qp3vq1qc5bp18uj | 10 d ago | JSON v1 |
| RADAR4Memory | 10.35097/7qp3vq1qc5bp18uj | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · radar service eu de | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:computer-science-ai | mapping · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · radar4memory radar service eu | connector:radar4memory_radar_service_eu@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · radar4memory radar service eu | connector:radar4memory_radar_service_eu@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · radar service eu de | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:imaging | enrichment · radar service eu de | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | /metadata/dc/description |
| license | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | /metadata/dc/rights |
| publication_date | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| title | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | /metadata/dc/title |