Projects per year
Abstract
Optical microscopes are an essential tool for both the detection of disease in clinics, and for scientific analysis. However, in much of the world access to high-performance microscopy is limited by both the upfront cost and maintenance cost of the equipment. Here we present an open-source, 3D-printed, and fully-automated laboratory microscope, with motorised sample positioning and focus control. The microscope is highly customisable, with a number of options readily available including trans- and epi- illumination, polarisation contrast imaging, and epi-florescence imaging. The OpenFlexure microscope has been designed to enable low-volume manufacturing and maintenance by local personnel, vastly increasing accessibility. We have produced over 100 microscopes in Tanzania and Kenya for educational, scientific, and clinical applications, demonstrating that local manufacturing can be a viable alternative to international supply chains that can often be costly, slow, and unreliable.
Original language | English |
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Pages (from-to) | 2447-2460 |
Number of pages | 14 |
Journal | Biomedical Optics Express |
Volume | 11 |
Issue number | 5 |
Early online date | 8 Apr 2020 |
DOIs | |
Publication status | Published - 1 May 2020 |
ASJC Scopus subject areas
- Biotechnology
- Atomic and Molecular Physics, and Optics
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UR Fellowship - Robotic microscopy for globally accessible science & healthcare
Bowman, R.
1/10/18 → 25/08/24
Project: Research council
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Robotic microscopy for globally accessible science and healthcare
Bowman, R., Harrington, K. & Stirling, J.
1/10/18 → 31/08/22
Project: Research council
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Automated microscopy for high-throughput malaria research.
Bowman, R. & Campbell, N.
Engineering and Physical Sciences Research Council
1/07/18 → 30/06/21
Project: Research council
Datasets
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Dataset for "Robotic microscopy for everyone: the OpenFlexure Microscope"
Collins, J. (Creator), Knapper, J. (Creator), Bowman, R. (Creator) & Mduda, J. (Data Collector), University of Bath, 23 Mar 2020
DOI: 10.15125/BATH-00734
Dataset