Label-free optical microscopy with artificial intelligence: a new paradigm in pathology
SignificancePathological examination is essential for diagnosing diseases in tissues such as cancer but involves labor-intensive and time-consuming processes. Label-free optical microscopy has emerged as a promising alternative that offers the ability to visualize tissue structures without the need for histochemical staining. Further, the integration of artificial intelligence (AI) into label-free microscopy has the potential to streamline the overall pathological diagnostic process.AimWe aim to review the use of AI-assisted label-free optical microscopy in revolutionizing pathological workflows.ApproachWe examine the integration of AI with label-free optical microscopy techniques and assess its overall impact on the pathological workflow. We evaluate how AI enhances each stage of label-free pathology, including specimen preparation, label-free imaging, virtual staining, and diagnostic analysis.ResultsLabel-free optical microscopy with AI has significantly improved the entire pathological workflow. AI assists specimen preparation with high efficiency, enhances label-free imaging with high resolution and speed, and enables cost-effective virtual staining with high throughput and automatic diagnostic analysis with high accuracy.ConclusionsAI-aided label-free optical microscopy enhances diagnostic speed, accuracy, and specimen preservation, offering a transformative approach that could redefine traditional pathology workflows and improve clinical outcomes.
Authors
- Chiho Yoon (ORCID: https://orcid.org/0000-0003-3971-3115)
- Eunwoo Park (ORCID: https://orcid.org/0000-0001-7954-7911)
- Byullee Park (ORCID: https://orcid.org/0000-0002-2949-1419)
- Donggyu Kim (ORCID: https://orcid.org/0000-0002-5395-1155)
Institutions
- Pohang University of Science and Technology (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Biophotonics discovery.
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1117/1.bios.2.2.020901
- Citations
- 15
- Primary Topic
- Optical Coherence Tomography Applications
- Type
- article
- Field-Weighted Citation Impact
- 10.11
Funders
- Ministry of Science and ICT, South Korea