Revisiting PSF models: Unifying framework and high-performance implementation.
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| Title: | Revisiting PSF models: Unifying framework and high-performance implementation. |
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| Authors: | Liu Y; Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland., Stergiopoulou V; Audiovisual Communications Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.; Galatea Laboratory, École Polytechnique Fédérale de Lausanne, Neuchâtel, Switzerland., Chuah J; Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland., Bezzam E; Audiovisual Communications Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland., Both GJ; HHMI Janelia Research Campus, Ashburn, Virginia, USA., Unser M; Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland., Sage D; Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland., Dong J; Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. |
| Source: | Journal of microscopy [J Microsc] 2025 Nov 04. Date of Electronic Publication: 2025 Nov 04. |
| Publication Model: | Ahead of Print |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Published for the Royal Microscopical Society by Blackwell Scientific Publications Country of Publication: England NLM ID: 0204522 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-2818 (Electronic) Linking ISSN: 00222720 NLM ISO Abbreviation: J Microsc Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Oxford, Published for the Royal Microscopical Society by Blackwell Scientific Publications. |
| Abstract: | Localisation microscopy often relies on detailed models of point-spread functions. For applications such as deconvolution or PSF engineering, accurate models for light propagation in imaging systems with a high numerical aperture are required. Different models have been proposed based on 2D Fourier transforms or 1D Bessel integrals. The most precise ones combine a vectorial description of the electric field and accurate aberration models. However, it may be unclear which model to choose as there is no comprehensive comparison between the Fourier and Bessel approaches yet. Moreover, many existing libraries are written in Java (e.g., our previous PSF generator software) or MATLAB, which hinders their integration into deep learning algorithms. In this work, we start from the original Richards-Wolf integral and revisit both approaches in a systematic way. We present a unifying framework in which we prove the equivalence between the Fourier and Bessel strategies and detail a variety of correction factors applicable to both of them. Then, we provide a high-performance implementation of our theoretical framework in the form of an open-source library that is built on top of PyTorch, a popular library for deep learning. It enables us to benchmark the accuracy and computational speed of different models and allows for an in-depth comparison of the existing models for the first time. We show that the Bessel strategy is optimal for axisymmetric beams, while the Fourier approach can be applied to more general scenarios. Our work enables the efficient computation of a point-spread function on CPU or GPU, which can then be included in simulation and optimisation pipelines. (© 2025 The Author(s). Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.) |
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| Grant Information: | CRSII5_213521 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; PZ00P2_216211 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung |
| Contributed Indexing: | Keywords: localisation microscopy; open‐source library; point‐spread function; vectorial field propagation |
| Entry Date(s): | Date Created: 20251104 Latest Revision: 20251104 |
| Update Code: | 20251104 |
| DOI: | 10.1111/jmi.70045 |
| PMID: | 41186941 |
| Database: | MEDLINE |
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