Artificial Intelligence for Label-Free Imaging and Spectroscopy in the Life Sciences
A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Biophotonics and Biomedical Optics".
Deadline for manuscript submissions: 1 June 2026 | Viewed by 774
Special Issue Editor
Interests: biophotonics; raman spectroscopy; label-free optical imaging; AI-powered biomedicine; morpho-molecular phenotyping; live cell imaging; data-driven bioimaging; multimodal optical microscopy; deep learning
Special Issue Information
Dear Colleagues,
Label-free optical microscopy and spectroscopy are powerful tools for investigating biological materials in a non-invasive and quantitative manner. However, the high-dimensional datasets produced by these techniques are often affected by noise, overlapping signals, and spurious background, creating barriers to extracting meaningful patterns, ensuring reliable interpretation, and achieving translational utility. Artificial Intelligence (AI) has emerged as a transformative solution, offering new strategies to obtain robust, interpretable insights from complex optical data and bridging the gap between photonics and life sciences.
We are pleased to invite you to contribute to this Special Issue, which seeks contributions that demonstrate how the synergy between AI and label-free optical imaging and spectroscopy can advance our understanding of life sciences. We welcome original research and review articles addressing both methodological innovations and application-driven studies. Emphasis will be placed on works that prioritize model transparency, generalizability, and biological relevance, with interpretable and physics-informed approaches encouraged.
The collection will focus on two main contribution areas:
- AI for biophotonic data preprocessing: AI-based methods for spectral and spatial denoising, background subtraction, and signal unmixing, particularly in low-SNR or complex biological environments.
- AI for biophotonic data analysis: AI-based quantitative analysis, including regression models to predict analyte concentrations and classification models for cell states, disease presence or stage, drug response, image segmentation, and more.
Relevant label-free optical techniques include, but are not limited to, the following: Raman, Brillouin, infrared, and photothermal spectroscopy; multi-harmonic and multiphoton fluorescence imaging; quantitative phase imaging; and optical coherence tomography. Applications may involve cells, tissues, organoids, pharmaceutical formulations, bioderived and bioinspired materials, or biohazards.
We look forward to receiving your contributions.
Dr. Arianna Bresci
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. Photonics is an international peer-reviewed open access monthly 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 2400 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
- artificial intelligence
- biphotonics
- label-free imaging
- machine learning
- microscopy
- spectroscopy
- optical biosensing
- data-driven photonics
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