ArticleQuantitative imaging in medicine and surgery2021
An automated and multiparametric algorithm for objective analysis of meibography images.
Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed, 46 citations in OpenAlex.
- Improved method for optical coherence tomography angiography: from reconstruction to clinical indicator quantification.Journal of biomedical optics · 2026Article
- Ophthalmic Segmentation and Analysis Software (OASIS): A Comprehensive Tool for Quantitative Evaluation of Meibography Images.Translational vision science & technology · 2025Article
- Development and multicenter validation of an AI driven model for quantitative meibomian gland evaluation.NPJ digital medicine · 2025Article
- A modular and adaptable approach for automated morphological feature extraction in meibography images.Scientific reports · 2025Article
- The repeatability of tests for dry eye signs and symptoms in the dry eye assessment and management (DREAM) study.Contact lens & anterior eye : the journal of the British Contact Lens Association · 2025Article
- Internal validation of a convolutional neural network pipeline for assessing meibomian gland structure from meibography.Optometry and vision science : official publication of the American Academy of Optometry · 2025Article
- A novel nomogram to predict glucocorticoid response in thyroid-associated ophthalmopathy: findings from a pilot study.Endocrine · 2024Article
- Quantitative evaluation of morphological and functional changes in meibomian glands and lipid layer thickness in patients with and without keratoconus.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Article
- Meibography signal intensity as a novel image biomarker for meibomian gland function: evidence from cross-sectional and longitudinal analyses.Quantitative imaging in medicine and surgery · 2024Article
- Global research of artificial intelligence in eyelid diseases: A bibliometric analysis.Heliyon · 2024Article
- Meibomian gland alterations in allergic conjunctivitis: insights from a novel quantitative analysis algorithm.Frontiers in cell and developmental biology · 2024Article
- Meibomian glands segmentation in infrared images with limited annotation.International journal of ophthalmology · 2024Article
- A Deep Learning Approach for Meibomian Gland Appearance Evaluation.Ophthalmology science · 2023Article
- Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features.Investigative ophthalmology & visual science · 2023Article
- Morphological changes in the meibomian gland in children with tic disorders.Quantitative imaging in medicine and surgery · 2023Article
- A deep learning-based model for automatic segmentation and evaluation of corneal neovascularization using slit-lamp anterior segment images.Quantitative imaging in medicine and surgery · 2023Article
- Meibomian gland stem/progenitor cells: The hunt for gland renewal.The ocular surface · 2023Article
- Development of Artefact-Free Imaging System for Accurate Meibomian Gland Reflectivity Assessment.Translational vision science & technology · 2023Article
- Impacts of gender and age on meibomian gland in aged people using artificial intelligence.Frontiers in cell and developmental biology · 2023Article
- Integration of Artificial Intelligence into the Approach for Diagnosis and Monitoring of Dry Eye Disease.Diagnostics (Basel, Switzerland) · 2022Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMeibography is a non-contact imaging technique used by ophthalmologists and eye care practitioners to acquire information on the characteristics of meibomian glands. One of its most important applications is to assist in the evaluation and diagnosis of meibomian gland dysfunction (MGD). As the artificial qualitative analysis of meibography images can lead to low repeatability and efficiency, automated and quantitative evaluation would greatly benefit the image analysis process. Moreover, since the morphology and function of meibomian glands varies at different stages of MGD, multiparametric analysis offering more comprehensive information could help in discovering subtle changes to glands during MGD progression. Therefore, an automated and multiparametric objective analysis of meibography images is urgently needed.
methodsAn algorithm was developed to perform multiparametric analysis of meibography images with fully automatic and repeatable segmentation based on image contrast enhancement and noise reduction. The full architecture can be divided into three steps: (I) segmentation of the tarsal conjunctiva area as the region of interest (ROI); (II) segmentation and identification of glands within the ROI; and (III) quantitative multiparametric analysis including a newly defined gland diameter deformation index (
resultsThe results of the performance evaluation between the manually defined ground truth and automatic segmentations were as follows: for ROI segmentation, the similarity index (
conclusionsA fully automated algorithm was developed which demonstrated high similarity with moderate segmentation errors for meibography image segmentation compared with the manual approach, offering multiple parameters to quantify the morphology and function of meibomian glands for the objective evaluation of meibography images.
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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.