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Diagnostics
Special Issues
Emerging Technologies and Diagnostic Innovations in Optometry and Vision Science
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Emerging Technologies and Diagnostic Innovations in Optometry and Vision Science

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Biomedical Optics".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 2139

Special Issue Editor

Prof. Dr. Shuan-Yu Huang

E-Mail Website
Guest Editor
Department of Optometry, Central Taiwan University of Science and Technology, Taichung 406, Taiwan
Interests: visual science; binocular vision; sports vision; optical design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will showcase recent advances in the diagnostic technologies, imaging modalities, and data-driven innovations reshaping optometry and vision science. We welcome original research, reviews, clinical studies, and technology-oriented papers in areas including the following:

  • Novel visual assessment tools and automated/mechanized diagnostic systems;
  • Advances in ocular imaging and multimodal diagnostics;
  • AI-based analysis and machine-learning decision support;
  • Accommodation–vergence assessment, binocular vision evaluation, and sports vision applications;
  • Visual rehabilitation, digital therapeutics, and technology-based training systems;
  • VR/AR platforms, wearable sensors, digital biomarkers, and smart medical devices;
  • Early detection, monitoring, and personalized management of refractive, binocular, and functional ocular disorders.

This interdisciplinary scope bridges clinical practice, instrument development, and data-driven research to advance modern eye care.

Prof. Dr. Shuan-Yu Huang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • optometry
  • vision diagnostics
  • ocular imaging
  • binocular vision
  • accommodation–vergence
  • AI in eye care
  • visual training
  • digital theranostics
  • sports vision
  • VR/AR
  • smart medical devices

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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12 pages, 1312 KB  
Article
Clinical Comparative Evaluation of Two New-Generation Optical Biometers: Intrasession Repeatability and Agreement of Biometric Parameters
by Farid J. Bedrán and David P. Piñero
Diagnostics 2026, 16(4), 526; https://doi.org/10.3390/diagnostics16040526 - 10 Feb 2026
Viewed by 468
Abstract
Objectives: This study aims to evaluate the intrasession repeatability of the HBM-1 (Huvitz) optical biometer and to assess its agreement with the IOLMaster 700 (Zeiss) for the main biometric parameters used in intraocular lens (IOL) power calculation and in myopia management. Methods: A [...] Read more.
Objectives: This study aims to evaluate the intrasession repeatability of the HBM-1 (Huvitz) optical biometer and to assess its agreement with the IOLMaster 700 (Zeiss) for the main biometric parameters used in intraocular lens (IOL) power calculation and in myopia management. Methods: A cross-sectional observational study was conducted in 82 eyes of 82 patients with the following age distribution: pediatric 26.8%, young adults 35.4%, and older adults 37.8% (total range 6–79 years). Optical biometry was performed three consecutive times with both biometers in the same session by a single trained examiner. HBM-1 repeatability was assessed using the within-subject standard deviation (Sw), the repeatability coefficient, and the intraclass correlation coefficient (ICC). Agreement between biometers was analyzed using Bland–Altman plots (limits of agreement, LoA). Results: The HBM-1 showed excellent intrasession repeatability, with very low Sw values—on the order of hundredths of a millimeter for axial length (AL), anterior chamber depth (ACD), and lens thickness (LT), and hundredths of a diopter for keratometry—with ICC ≥ 0.97 for most parameters. The mean bias (HBM-1 vs. IOLMaster 700) was small: AL 0.012 ± 0.052 mm (p = 0.045; LoA: −0.09 to 0.11 mm), ACD 0.059 ± 0.068 mm (p < 0.001; −0.07 to 0.19 mm), LT 0.052 ± 0.090 mm (p < 0.001; −0.12 to 0.23 mm), and central corneal thickness 0.82 ± 7.12 μm (p = 0.301; −13.1 to 14.8 μm). For corneal diameter and corneal curvature, mean differences were small (≤0.07 D) and not statistically significant in most cases. Age was not associated with discrepancies in AL but showed weak correlations with some anterior segment differences, without clear clinical relevance. Conclusions: The HBM-1 demonstrated excellent intrasession repeatability and a good level of clinical agreement with the IOLMaster 700 in a broad population that included children, young adults, and older adults. Full article
(This article belongs to the Special Issue Emerging Technologies and Diagnostic Innovations in Optometry and Vision Science)
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Review

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15 pages, 1217 KB  
Review
Applications of Artificial Intelligence in Corneal Nerve Images in Ophthalmology
by Raul Hernan Barcelo-Canton, Mingyi Yu, Chang Liu, Aya Takahashi, Isabelle Xin Yu Lee and Yu-Chi Liu
Diagnostics 2026, 16(4), 602; https://doi.org/10.3390/diagnostics16040602 - 18 Feb 2026
Viewed by 498
Abstract
Corneal nerves (CNs) are essential to maintain corneal epithelial integrity and ocular surface homeostasis. In vivo confocal microscopy (IVCM) enables the acquisition of high-resolution visualization of CNs, allowing visualization on a microscopic level. Traditionally, CN images must be analyzed by manual examination, which [...] Read more.
Corneal nerves (CNs) are essential to maintain corneal epithelial integrity and ocular surface homeostasis. In vivo confocal microscopy (IVCM) enables the acquisition of high-resolution visualization of CNs, allowing visualization on a microscopic level. Traditionally, CN images must be analyzed by manual examination, which is time consuming and labor intensive. Artificial intelligence (AI) has facilitated reliable analysis of CN parameters, allowing for automatic and semiautomatic analysis of CNs. These include the identification, segmentation, and quantitative analysis of various CN parameters. This review summarizes the applications of AI-driven, automatic, and semiautomatic models in the CN analysis of IVCM images while also focusing on their diagnostic relevance in dry eye disease (DED) and neuropathic corneal pain (NCP). Recent advancements in AI have transformed IVCM image analysis by improving reproducibility and reducing operator dependency and time. The AI-based algorithm has been demonstrated to have good performance and sensitivity to identify and quantify the CN metrics. AI has also been utilized to improve the diagnostic accuracy of DED with IVCM scans, involving multiple portions of the CNs, such as the inferior whorl region. When employed with IVCM images of patients with NCP, AI-assisted identification of microneuromas and changes in CN metrics has provided an improvement in diagnostic accuracy. Despite promising advances and outcomes, the widespread implementation of these AI models in CN image analysis requires large-scale validation. Future integration of multimodal AI algorithms remains a promising endeavor to enhance diagnostic accuracy and disease stratification. Full article
(This article belongs to the Special Issue Emerging Technologies and Diagnostic Innovations in Optometry and Vision Science)
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