Projects per year
Abstract
The OpenFlexure Microscope is a 3D-printed, low-cost microscope capable of automated image acquisition through the use of a motorised translation stage and a Raspberry Pi imaging system. This automation has applications in research and healthcare, including in supporting the diagnosis of malaria in low-resource settings. The plasmodium parasites that cause malaria require high magnification imaging, which has a shallow depth of field, necessitating the development of an accurate and precise autofocus procedure. We present methods of identifying the focal plane of the microscope, and procedures for reliably acquiring a stack of focused images on a system affected by backlash and drift. We also present and assess a method to verify the success of autofocus during the scan. The speed, reliability and precision of each method are evaluated, and the limitations discussed in terms of the end users' requirements.
Original language | English |
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Pages (from-to) | 29-39 |
Number of pages | 11 |
Journal | Journal Of Microscopy |
Volume | 285 |
Issue number | 1 |
Early online date | 9 Oct 2021 |
DOIs | |
Publication status | Published - 31 Jan 2022 |
Bibliographical note
Funding Information:We acknowledge financial support from EPSRC (EP/R013969/1, EP/R011443/1) and The Royal Society (URF\R1\180153).
Keywords
- autofocus
- focus
- light microscopy
- open hardware
- open source
ASJC Scopus subject areas
- Pathology and Forensic Medicine
- Histology
Fingerprint
Dive into the research topics of 'Fast, high-precision autofocus on a motorised microscope: Automating blood sample imaging on the OpenFlexure Microscope'. Together they form a unique fingerprint.Projects
- 1 Finished
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Detailed Malaria Diagnostics with Intelligent Microscopy
Bowman, R. (PI) & Campbell, N. (CoI)
Engineering and Physical Sciences Research Council
1/02/18 → 31/01/22
Project: Research council
Datasets
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Dataset for Fast, high precision autofocus on a motorised microscope: Automating blood sample imaging on the OpenFlexure Microscope
Knapper, J. (Creator) & Bowman, R. (Supervisor), University of Bath, 9 Oct 2021
DOI: 10.15125/BATH-01063, https://gitlab.com/jaknapper/z-step-measurements and one more link, https://doi.org/10.5281/zenodo.5564503 (show fewer)
Dataset