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Diagnostics
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New Advances in Hyperspectral and Multispectral Imaging for Diseases Diagnosis
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New Advances in Hyperspectral and Multispectral Imaging for Diseases Diagnosis

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

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2852

Special Issue Editor

Dr. Arvind Mukundan

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
Interests: hyperspectral imaging; CAD-modeling; control and instrumentation

Special Issue Information

Dear Colleagues,

Spectral imaging is a revolutionary tool in medical diagnostics that provides an unmatched capacity to visualize and analyze biological tissues and diseases. The primary objective of this Special Issue is to investigate the diverse functions of spectrum imaging in the field of diagnosis, emphasizing its uses, advantages, and difficulties across different medical disciplines. Spectral imaging is revolutionizing modern diagnostics by improving disease detection accuracy, facilitating early intervention, and enabling tailored treatment strategies. This Special Issue will specifically concentrate on advancements in hyperspectral imaging (HSI) and multispectral imaging (MSI). Hyperspectral imaging, by capturing a broad range of light wavelengths, offers precise data that can be utilized to detect even the most minor alterations in tissue composition and structure. Although multispectral imaging captures a smaller number of spectral bands, it provides notable advantages in clinical environments due to its streamlined data processing and quicker acquisition periods. This Special Issue solicits original research articles, comprehensive reviews, case studies, and technical comments that explore the creative uses of hyperspectral and multispectral imaging in medical diagnostics. We particularly appreciate contributions that address improvements in these technologies, their integration with other diagnostic modalities, clinical outcomes, and future directions.

  1. Applications of Spectral Imaging in Oncology Diagnostics;
  2. Spectral Imaging for Early Detection of Neurodegenerative Diseases;
  3. Non-Invasive Skin Cancer Diagnosis Using Spectral Imaging in Dermatology;
  4. Advancements in Spectral Imaging for Cardiovascular Disease Detection;
  5. Enhancing Diagnostic Accuracy with AI-Integrated Hyperspectral and Multi-spectral Imaging;
  6. Early Detection of Retinal Diseases through Spectral Imaging in Ophthalmology;
  7. Spectral Imaging in Pathology: Improving Tissue Analysis and Disease Identification;
  8. Hyperspectral Imaging for the Identification of Infectious Diseases;
  9. Comparative Effectiveness of Hyperspectral and Multispectral Imaging in Gastrointestinal Diagnostics;
  10. Development of Portable Spectral Imaging Devices for Point-of-Care Diagnostics.

Dr. Arvind Mukundan
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 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. 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

  • spectral imaging
  • hyperspectral imaging (HSI)
  • multispectral imaging (MSI)
  • medical diagnostics
  • disease detection
  • clinical applications
  • imaging technology
  • early diagnosis
  • personalized medicine
  • diagnostic pathways
  • healthcare innovations
  • biomedical imaging

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Published Papers (2 papers)

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Research

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25 pages, 9319 KiB  
Article
Blind Separation of Skin Chromophores from Multispectral Dermatological Images
by Mustapha Zokay and Hicham Saylani
Diagnostics 2024, 14(20), 2288; https://doi.org/10.3390/diagnostics14202288 - 14 Oct 2024
Viewed by 917
Abstract
Background/Objectives: Based on Blind Source Separation and the use of multispectral imaging, the new approach we propose in this paper aims to improve the estimation of the concentrations of the main skin chromophores (melanin, oxyhemoglobin and deoxyhemoglobin), while considering shading as a [...] Read more.
Background/Objectives: Based on Blind Source Separation and the use of multispectral imaging, the new approach we propose in this paper aims to improve the estimation of the concentrations of the main skin chromophores (melanin, oxyhemoglobin and deoxyhemoglobin), while considering shading as a fully-fledged source. Methods: In this paper, we demonstrate that the use of the Infra-Red spectral band, in addition to the traditional RGB spectral bands of dermatological images, allows us to model the image provided by each spectral band as a mixture of the concentrations of the three chromophores in addition to that of the shading, which are estimated through four steps using Blind Source Separation. Results: We studied the performance of our new method on a database of real multispectral dermatological images of melanoma by proposing a new quantitative performances measurement criterion based on mutual information. We then validated these performances on a database of multispectral dermatological images that we simulated using our own new protocol. Conclusions: All the results obtained demonstrated the effectiveness of our new approach for estimating the concentrations of the skin chromophores from a multispectral dermatological image, compared to traditional approaches that consist of using only the RGB image by neglecting shading. Full article
(This article belongs to the Special Issue New Advances in Hyperspectral and Multispectral Imaging for Diseases Diagnosis)
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Review

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16 pages, 897 KiB  
Review
Application of Raman Spectroscopy in Non-Invasive Analysis of the Gut Microbiota and Its Impact on Gastrointestinal Health
by Patrycja Krynicka, George Koulaouzidis, Karolina Skonieczna-Żydecka, Wojciech Marlicz and Anastasios Koulaouzidis
Diagnostics 2025, 15(3), 292; https://doi.org/10.3390/diagnostics15030292 - 26 Jan 2025
Cited by 1 | Viewed by 1318
Abstract
The gut microbiota, a complex community of microorganisms, plays a crucial role in gastrointestinal (GI) health, influencing digestion, metabolism, immune function, and the gut–brain axis. Dysbiosis, or an imbalance in microbiota composition, is associated with GI disorders, including irritable bowel syndrome (IBS), inflammatory [...] Read more.
The gut microbiota, a complex community of microorganisms, plays a crucial role in gastrointestinal (GI) health, influencing digestion, metabolism, immune function, and the gut–brain axis. Dysbiosis, or an imbalance in microbiota composition, is associated with GI disorders, including irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and colorectal cancer (CRC). Conventional microbiota analysis methods, such as next-generation sequencing (NGS) and nuclear magnetic resonance (NMR), provide valuable insights but are often expensive, time-consuming, and destructive. Raman spectroscopy (RS) is a non-invasive, cost-effective, and highly sensitive alternative. This analytical technique relies on inelastic light scattering to generate molecular “fingerprints”, enabling real-time, marker-free analysis of microbiota composition and metabolic activity. This review explores the principles, sample preparation techniques, and advancements in RS, including surface-enhanced Raman spectroscopy (SERS), for microbiota research. RS facilitates identifying microbial species, analysing key metabolites like short-chain fatty acids (SCFA), and monitoring microbiota responses to dietary and therapeutic interventions. The comparative analysis highlights RS’s advantages over conventional techniques, such as the minimal sample preparation, real-time capabilities, and non-destructive nature. The integration of RS with machine learning enhances its diagnostic potential, enabling biomarker discovery and personalised treatment strategies for GI disorders. Challenges, including weak Raman signals and spectral complexity, are discussed alongside emerging solutions. As RS technology advances, mainly through portable spectrometers and AI integration, its clinical application in microbiota diagnostics and personalised medicine is poised to transform GI healthcare, bridging microbiota research with practical therapeutic strategies. Full article
(This article belongs to the Special Issue New Advances in Hyperspectral and Multispectral Imaging for Diseases Diagnosis)
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