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A cost-effective, out-of-the-box photon counting platform for multi-photon in vivo microscopy applications

Project description

Microscope add-on enhances the resolution imaging of large tissue volumes

Multi-photon microscopy is a laser-based technique which peers deep into the brain. Trying to capture cellular activity across large tissue volumes with multi-photon microscopy induces faster imaging. As a result, fewer and fewer photons become available to form images. The challenge therefore lies in trying to obtain meaningful images under these dim conditions. A detector-readout method called photon counting could tackle this issue; however, its implementation requires extensive electronics knowledge and custom components. The EU-funded PySightBox project plans to commercialise PySight, a hardware and open-source software solution whose easy installation procedure and integration with state-of-the-art hardware eliminate such concerns. Using PySight, microscopists can conduct rapid imaging of large volumes over long sessions, without compromising spatial or temporal resolution.


Multi-photon microscopy is the gold-standard brain imaging approach to study the brain and other organs in action and is used across hundreds of laboratories worldwide. The current attempts to imaging increasingly large tissue volumes pushed multi-photon microscopy into the photon-deprived regime (i.e. the dim conditions that result from moving faster allowing collection of less photons per pixel/voxel). Under these condition, the relative few photons detected can be lost in the electronics noise of the system. Photon-counting techniques overcome this hurdle yet its implementation requires either custom electronics (and electronics expertise) or the use of relative expensive commercial solutions that are not tailored for this type of imaging thus providing only a partial solution. Therefore there is an unmet need in the market today for an easy to implement photon counting solution that seamlessly integrates into existing imaging setups and provides all the required software to perform intravital multi-dimensional imaging. This project aims to commercialize PySight, an add-on hardware and software solution tailored exactly to fill this market gap. Moreover, the product I propose to develop here targets both the academic and medical sectors as multi-photon diagnostic are becoming more common nowadays. Beyond achieving the unmet needs, our prototype improves many aspects of imaging (such a neuronal population imaging in single and rapid volumetric imaging). Its spatio-temporal resolution outperforms top-tier imaging setups while retaining over 200 times lower data rates. Importantly, PySight requires no electronics expertise and its software is open-source.

Funding Scheme



Net EU contribution
€ 150 000,00
Other funding
€ 0,00

Beneficiaries (1)