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Optics
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Advancements in Optical Imaging and Sensing for Biomedical and Environmental...
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Advancements in Optical Imaging and Sensing for Biomedical and Environmental Applications

A special issue of Optics (ISSN 2673-3269).

Deadline for manuscript submissions: 31 December 2025 | Viewed by 739

Special Issue Editors

Dr. Zhen Ding

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Guest Editor
School of Computer and Control Engineering, Northeast Forestry University, Harbin, China
Interests: machine vision; physiological big data analysis; intelligent ergonomics
Dr. Wei Zhang

E-Mail
Guest Editor Assistant
Department of Clinical Science, Intervention and Technology, Karolinska Institute, Stockholm, Sweden
Interests: deep learning; medical image processing
Dr. Chen Hui

E-Mail Website
Guest Editor Assistant
School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
Interests: deep learning; image compression; image quality assessment; video compression

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the latest advancements in optical imaging and sensing technologies, aiming to showcase innovative methods and applications that address current challenges in biomedical, environmental, and industrial contexts. Recent developments in photonics, quantum optics, and artificial intelligence are transforming the landscape of optical technologies, providing unprecedented precision, speed, and versatility in data acquisition and analysis. Topics of interest include but are not limited to the following: 

  • Novel optical imaging modalities (e.g., hyperspectral imaging, super-resolution imaging);
  • Optical sensors and photonic systems for medical diagnostics and environmental monitoring;
  • Nonlinear and quantum optical techniques for advanced imaging and sensing;
  • Integration of machine learning and deep learning in optical data processing;
  • Multimodal imaging systems and their applications;
  • Techniques for enhancing imaging resolution and reducing noise in challenging environments.

The goal of this Special Issue is to provide a platform for researchers to share their findings and insights, fostering collaboration and innovation in the optics and photonics community. Original research articles, reviews, and case studies are welcome.

Dr. Zhen Ding
Guest Editor

Dr. Wei Zhang
Dr. Chen Hui
Guest Editor Assistants

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Optics is an international peer-reviewed open access quarterly 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 1200 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

  • optical imaging
  • sensing
  • quantum optics
  • machine learning
  • deep learning
  • medical diagnostics
  • environmental monitoring

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (1 paper)

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Research

17 pages, 3845 KB  
Article
Dual-Generator and Dynamically Fused Discriminators Adversarial Network to Create Synthetic Coronary Optical Coherence Tomography Images for Coronary Artery Disease Classification
by Junaid Zafar, Faisal Sharif and Haroon Zafar
Optics 2025, 6(3), 38; https://doi.org/10.3390/opt6030038 - 14 Aug 2025
Viewed by 291
Abstract
Deep neural networks have led to a substantial increase in multifaceted classification tasks by making use of large-scale and diverse annotated datasets. However, diverse optical coherence tomography (OCT) datasets in cardiovascular imaging remain an uphill task. This research focuses on improving the diversity [...] Read more.
Deep neural networks have led to a substantial increase in multifaceted classification tasks by making use of large-scale and diverse annotated datasets. However, diverse optical coherence tomography (OCT) datasets in cardiovascular imaging remain an uphill task. This research focuses on improving the diversity and generalization ability of augmentation architectures while maintaining the baseline classification accuracy for coronary atrial plaques using a novel dual-generator and dynamically fused discriminator conditional generative adversarial network (DGDFGAN). Our method is demonstrated on an augmented OCT dataset with 6900 images. With dual generators, our network provides the diverse outputs for the same input condition, as each generator acts as a regulator for the other. In our model, this mutual regularization enhances the ability of both generators to generalize better across different features. The fusion discriminators use one discriminator for classification purposes, hence avoiding the need for a separate deep architecture. A loss function, including the SSIM loss and FID scores, confirms that perfect synthetic OCT image aliases are created. We optimize our model via the gray wolf optimizer during model training. Furthermore, an inter-comparison and recorded SSID loss of 0.9542 ± 0.008 and a FID score of 7 are suggestive of better diversity and generation characteristics that outperform the performance of leading GAN architectures. We trust that our approach is practically viable and thus assists professionals in informed decision making in clinical settings. Full article
(This article belongs to the Special Issue Advancements in Optical Imaging and Sensing for Biomedical and Environmental Applications)
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