Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

Cells. 2022 Nov 18;11(22):3670. doi: 10.3390/cells11223670.


In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.

Keywords: computational imaging; point-of-care-test; portable microscope.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Lenses*
  • Microscopy* / methods
  • Microscopy, Interference
  • Point-of-Care Systems

Grant support

This study is partially supported by National Natural Science Foundation of China (NSFC) (62005120), the Natural Science Foundation of Jiangsu Province (BK2019045, BK20201305), and Suzhou Science and Technology Development Project (SYSD2020132), and Biopharmaceutical Industry Innovation (Clinical Trial Capability Improve-ment)->Medicine-Industrial Collaborative Innovation Research Project (SLJ2022019).