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Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

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Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

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Optofluidic imaging meets deep learning: from merging to emerging.

Dickson M D Siu¹, Kelvin C M Lee¹, Bob M F Chung²

¹Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong. tsia@hku.hk.

|January 5, 2023

Summary

This summary is machine-generated.

Advanced optical microscopy and deep learning (DL) are transforming lab-on-a-chip imaging into a smart engine. This review explores integrating these technologies for enhanced image formation, analytics, and autonomous applications.

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Area of Science:

Optofluidics
Biomedical Engineering
Analytical Chemistry

Background:

Lab-on-a-chip (LOC) imaging has evolved from basic inspection to a sophisticated analytical tool.
Advances in optical microscopy enable high-resolution imaging across diverse scales and timeframes.
Deep learning (DL) algorithms have revolutionized complex image processing and analysis.

Purpose of the Study:

To review the latest trends in optical microscopy and DL for LOC imaging (optofluidic imaging).
To discuss the integration of advanced imaging techniques and DL algorithms for tailored LOC applications.
To highlight synergistic opportunities between optofluidic imaging and DL.

Main Methods:

Review of current literature on optical microscopy and DL in LOC systems.
Analysis of the integration of imaging techniques and DL algorithms.
Identification of key areas for synergistic development in optofluidic imaging.

Main Results:

Optical microscopy and DL offer unprecedented capabilities for LOC imaging.
Synergies exist in image formation, image analytics, and intelligent image-guided autonomous LOC systems.
The integration promises enhanced analytical chemistry, biological discovery, and clinical applications.

Conclusions:

Optofluidic imaging, powered by DL, represents a significant advancement in LOC technology.
Future frontiers lie in intelligent image formation, advanced analytics, and autonomous systems.
These integrated approaches will drive innovation in scientific research and clinical diagnostics.