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Updated: May 19, 2026
07:27
Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy (DHM)
Published on: November 1, 2017
AI-driven digital holographic microscopy for label-free quantitative cellular analysis: toward low-cost and
1Department of Robotics & Mechatronics Engineering, DGIST, Daegu 42988, Republic of Korea.
Biomedical Optics Express
|May 18, 2026
Summary
Artificial intelligence (AI) and digital holographic microscopy (DHM) offer precise, label-free cellular imaging. AI-enhanced DHM provides real-time, portable solutions for biomedical diagnostics and cell analysis.
Area of Science:
- Biomedical Imaging
- Artificial Intelligence
- Optical Microscopy
Background:
- Digital holographic microscopy (DHM) enables label-free, noninvasive cellular imaging.
- Advancements in AI are crucial for enhancing DHM's capabilities.
Purpose of the Study:
- To review AI-driven DHM technologies for cellular imaging and analysis.
- To explore AI's role in phase reconstruction and biomedical applications of DHM.
Main Methods:
- Deep generative and diffusion models for enhanced phase retrieval.
- AI-assisted quantitative phenotyping for cell analysis.
- Integration of AI with DHM for real-time imaging.
Main Results:
- AI significantly improves phase retrieval accuracy in DHM.
- AI enables high-accuracy classification of blood and cancer cells.
- Label-free evaluation of cardiomyocyte function and drug response is achieved.
Conclusions:
- AI-integrated DHM offers scalable, accessible technology for practical biomedical diagnostics.
- Future DHM platforms will be low-cost, edge-AI-enabled for point-of-care applications.
- Challenges include data standardization, interpretability, and multimodal integration.
