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Label-free optical microscopy with artificial intelligence: a new paradigm in pathology.
Chiho Yoon1, Eunwoo Park1, Donggyu Kim1
1Pohang University of Science and Technology (POSTECH), Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Departments of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, Pohang, Republic of Korea.
Artificial intelligence (AI) combined with label-free optical microscopy significantly enhances pathology workflows. This AI-driven approach improves diagnostic speed, accuracy, and specimen preservation for better patient outcomes.
Area of Science:
- Pathology
- Biomedical Imaging
- Artificial Intelligence
Background:
- Traditional pathological examination is labor-intensive and time-consuming.
- Label-free optical microscopy offers unstained tissue visualization.
- Integrating artificial intelligence (AI) can streamline pathology.
Purpose of the Study:
- To review AI-assisted label-free optical microscopy in pathology.
- To assess AI's impact on pathological workflows.
Main Methods:
- Examining AI integration with label-free optical microscopy.
- Evaluating AI's enhancement of specimen preparation, imaging, virtual staining, and diagnostic analysis.
Main Results:
- AI significantly improves the pathological workflow.
- AI enhances specimen preparation efficiency and label-free imaging resolution/speed.
- AI enables cost-effective virtual staining and accurate automated diagnostics.
Conclusions:
- AI-aided label-free microscopy boosts diagnostic speed and accuracy.
- This approach enhances specimen preservation, potentially redefining pathology.
- The integration promises improved clinical outcomes.
