Multicentre Pixel-Level Tear Meniscus Segmentation Dataset with Multimodal Imaging for Dry Eye Diagnosis
Xiaoyu Chen, Kesheng Wang, Kunhui Xu, Chun Xiao, Ying Wang, Shoujun Huang, Weihua Yang, Qi Dai · 2025
Read Multicentre Pixel-Level Tear Meniscus Segmentation Dataset with Multimodal Imaging for Dry Eye Diagnosis by Xiaoyu Chen, Kesheng Wang, Kunhui Xu, Chun Xiao, Ying Wang, Shoujun Huang, Weihua Yang, Qi Dai (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12864915.txt.
Description
Xiaoyu Chen and co-authors release a public data set for teaching machines to outline the tear meniscus, the thin strip of tear fluid whose height betrays dry eye. Their 2025 paper starts from the diagnosis: meniscus height is a standard sign of tear supply and stability, but it is still measured by hand. Automated reading needs labeled images, and none were public for this task.
Five Chinese centers supplied about 1,700 color images and as many infrared ones. Each carries a pixel-level outline drawn through a new human-computer workflow the team built. The authors call it the only open multimodal set of its kind. They offer it to standardize image banks and push dry eye research.
Catalog record
| CREATOR | Xiaoyu Chen, Kesheng Wang, Kunhui Xu, Chun Xiao, Ying Wang, Shoujun Huang, Weihua Yang, Qi Dai |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 23 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |