| EPSRC Reference: |
EP/R025398/1 |
| Title: |
Computational microscopy in Cambridge Advanced Imaging Centre |
| Principal Investigator: |
Muresan, Dr L |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Physiology Development and Neuroscience |
| Organisation: |
University of Cambridge |
| Scheme: |
EPSRC Fellowship |
| Starts: |
01 January 2018 |
Ends: |
31 December 2022 |
Value (£): |
450,498
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| EPSRC Research Topic Classifications: |
| Instrumentation Eng. & Dev. |
Mathematical Analysis |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
A current trend in light microscopy design is to overcome the instrument's limitations via computational methods. The "intelligent" microscopes I envisage with this project will be able to adapt in real time their imaging parameters with respect to the sample being imaged. This will allow, for example, to reduce the damage inflicted to living samples or to selectively image interesting regions, allowing them to be imaged faster or at higher resolution. Furthermore, via computational microscopy enhanced information can be inferred from raw images by running specialised software. There is a need of bespoke software to be designed and implemented, adapted to the novel techniques developed in CAIC.
This project focuses on creating software for intelligent microscopes. The software development will be tightly integrated with the design of microscopes in CAIC, and with the work of the project partners, experts in applied mathematics, machine learning, biophysics and optics. Some of the instruments, such as light sheet microscopes, are able to generate huge amounts of data, on the order of terabytes for a single experiment. It is crucial that the software can cope with such large datasets and to do so in a reasonable amount of time. In order to achieve this goal, we will make extensive use of the High Performance Computing Centre in Cambridge, that provides high-throughput and GPU computing.
Another example of computational microscopy is the reconstruction of images with sub-pixel accuracy. One example is single molecule localisation microscopy, whose inventors were awarded the Nobel prize in Chemistry in 2014. CAIC and partners are involved in several projects utilising this technique, and adapted solutions for visualisation, detection; localisation and tracking of single molecules are essential for their success. Finally, computational microscopy will be applied to fuse information of several multi-modal images.
Software that can be used as stand-alone tools will be made available on CAIC's website and in software repositories. Several meetings will be organised, to communicate project results as well as to exchange ideas in the microscopy image analysis community. These meetings will take the form of workshops, trainings and software clubs. Graduate students will be involved in several sub-projects, to acquire hands-on experience in software development for microscopy image analysis.
Building on the experience of this project, the aim is to nucleate a sustainable research infrastructure for computational microscopy in Cambridge Advanced Imaging Centre.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.cam.ac.uk |