ArticleJournal of biophotonics2018
Automated three-dimensional cell counting method for grading uveitis of rodent eye in vivo with optical coherence tomography.
Article in Journal of biophotonics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Convolutional neural network-based differentiation of intraocular inflammatory cells with ultrahigh-resolution OCT.Biomedical optics express · 2025Article
- Novel Artificial Intelligence-Based Quantification of Anterior Chamber Inflammation Using Vision Transformers.Translational vision science & technology · 2025Article
- Comprehensive Grading System for Experimental Autoimmune Uveitis in Mice.Biomedicines · 2023Article
- Artificial confocal microscopy for deep label-free imaging.Nature photonics · 2023Article
- Effect of Fas and Bcl-2 DNA Damages Response Expression in Stem Cells on Apoptosis of Nucleus Pulposus of Intervertebral Disc.Stem cells international · 2023Article
- Recent advances in optical coherence tomography for anterior segment imaging in small animals and their clinical implications.The ocular surface · 2022Review
- Grading Anterior Chamber Inflammation with Anterior Segment Optical Coherence Tomography: An Overview.Ocular immunology and inflammation · 2022Article
- Article
- Quantitative Assessment of Experimental Ocular Inflammatory Disease.Frontiers in immunology · 2021Review
- Development, Validation, and Innovation in Ophthalmic Laser-Based Imaging: Report From a US Food and Drug Administration-Cosponsored Forum.JAMA ophthalmology · 2021Article
- Ocular anterior chamber blood cell population differentiation using spectroscopic optical coherence tomography.Biomedical optics express · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
In preclinical vision research, cell grading in small animal models is essential for the quantitative evaluation of intraocular inflammation. Here, we present a new and practical optical coherence tomography (OCT) image analysis method for the automated detection and counting of aqueous cells in the anterior chamber (AC) of a rodent model of uveitis. Anterior segment OCT images are acquired with a 100 kHz swept-source OCT system. The proposed method consists of 2 steps. In the first step, we first despeckle and binarize each OCT image. After removing AS structures in the binary image, we then apply area thresholding to isolate cell-like objects. Potential cell candidates are selected based on their best fit to roundness. The second step performs the cell counting within the whole AC, in which additional cell tracking analysis is conducted on the successive OCT images to eliminate redundancy in cell counting. Finally, 3D cell grading using the proposed method is demonstrated in longitudinal OCT imaging of a mouse model of anterior uveitis in vivo. Rendering of anterior segment (orange) of mouse eye and automatically counted anterior chamber cells (green). Inset is a top view of the rendering, showing the cell distribution across the anterior chamber.
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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.