ArticleBiomedical optics express2023
Corneal endothelium assessment in specular microscopy images with Fuchs' dystrophy via deep regression of signed distance maps.
Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Current Applications of Artificial Intelligence for Fuchs Endothelial Corneal Dystrophy: A Systematic Review.Translational vision science & technology · 2025Pooled it
- A Topology-Aware Extension of Guttae Area Ratio in Fuchs Endothelial Corneal Dystrophy.Translational vision science & technology · 2026Article
- Validation of Automated Software for Guttae Quantification in Fuchs Endothelial Corneal Dystrophy.Translational vision science & technology · 2026Article
- Recent advances in corneal specular microscopy image analysis through artificial intelligence.PLOS digital health · 2026Review
- Artificial intelligence in corneal endothelial disease and endothelial keratoplasty: current evidence, clinical readiness, and future directions.Frontiers in ophthalmology · 2026Review
- Artificial Intelligence Application in Cornea and External Diseases.Diagnostics (Basel, Switzerland) · 2025Review
- Deep learning for detection of Fuchs endothelial dystrophy from widefield specular microscopy imaging: a pilot study.Eye and vision (London, England) · 2024Article
- Article
- Corneal endothelium assessment in specular microscopy images with Fuchs' dystrophy via deep regression of signed distance maps.Biomedical optics express · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 6 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Specular microscopy assessment of the human corneal endothelium (CE) in Fuchs' dystrophy is challenging due to the presence of dark image regions called guttae. This paper proposes a UNet-based segmentation approach that requires minimal post-processing and achieves reliable CE morphometric assessment and guttae identification across all degrees of Fuchs' dystrophy. We cast the segmentation problem as a regression task of the cell and gutta signed distance maps instead of a pixel-level classification task as typically done with UNets. Compared to the conventional UNet classification approach, the distance-map regression approach converges faster in clinically relevant parameters. It also produces morphometric parameters that agree with the manually-segmented ground-truth data, namely the average cell density difference of -41.9 cells/mm
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.