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Smart microscopy: adaptive microscope control to improve the way we see life
Alfredo Rates1, Josiah B Passmore1, Nils Norlin2
1Cell Biology, Neurobiology and Biophysics, Department of Biology, Utrecht University, Utrecht, The Netherlands.
Npj Imaging
|March 3, 2026
Summary
Smart microscopy integrates real-time analysis, feedback control, and automated actuation. This approach enhances experimental flexibility by adapting settings for optimal resolution, speed, and sample health in biological research.
Area of Science:
- Integrates biology, optics, engineering, and computer science for advanced imaging.
- Focuses on the development of intelligent microscopy systems.
Background:
- Traditional microscopes have fixed acquisition settings.
- Smart microscopy systems adapt in real-time based on sample data.
- Enables navigation of competing experimental demands like resolution, speed, and sample health.
Purpose of the Study:
- To present a practical framework defining "smart" microscopy.
- To classify smart microscopy approaches by experimental goals.
- To guide the implementation of smart microscopy in life sciences.
Main Methods:
- Defines smart microscopy as real-time analysis, feedback control, and automated actuation.
- Classifies approaches by experimental goals: quality-, event-, target-, information-, or outcome-driven.
- Discusses strategies for analysis and control within these classifications.
Main Results:
- Smart microscopy offers adaptive acquisition for improved experimental outcomes.
- A classification framework aids in selecting appropriate smart microscopy strategies.
- Identifies key challenges and opportunities for wider adoption.
Conclusions:
- Smart microscopy represents a significant advancement over traditional methods.
- Community-driven efforts are crucial for accessibility and adoption.
- Smart microscopy promises to broaden its impact across life science research.
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