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GPU implementation of full vectorial Point Spread Function (PSF) fitting

Super-resolution microscopy is a technique in optical microscopy that enables one to go beyond the diffraction limit of light. At the core of super-resolution microscopy lies the fitting of the Point Spread Function (PSF). This is a compute-intensive task, but it is also highly parallelizable, making it ideally suited for modern computing architectures.

Previously, a model for the PSF was implemented in MATLAB. However, while this implementation gave highly promising results, the approach faced limitations in processing speed and memory usage. This, in turn, limited the achievable resolutions.

This project aims to develop a full vectorial PSF model for both multi-core CPUs and CUDA-enabled GPUs. With the project, we aim to significantly enhance the efficiency and accuracy of super-resolution microscopy. The outcome of this project is a scalable and versatile super-resolution microscopy software that is open-source and can be adapted to various research needs.

Participating organisations

Delft University of Technology
Netherlands eScience Center
Natural Sciences & Engineering
Natural Sciences & Engineering



Stijn Heldens
Bernd Rieger
Lead Applicant
Delft University of Technology
Sjoerd Stallinga
Ben van Werkhoven
Ben van Werkhoven
Lead RSE
Netherlands eScience Center
Awoke A. Negash
Postdoctoral researcher
Delft University of Technology
Isabel Droste
PhD student
TU Delft
Ronald Ligteringen
ICT support
TU Delft
Niels  Drost
Niels Drost
Programme Manager
Netherlands eScience Center

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Updated 8 months ago
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