{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/noninvasive-megapixel-fluorescence-microscopy","title":"Noninvasive megapixel fluorescence microscopy through scattering layers by a virtual reflection-matrix","arxiv_id":"2312.16065","date":"2023-12-26","proceeding":null,"authors":["Gil Weinberg","Elad Sunray","Ori Katz"],"abstract":"Optical-resolution fluorescence imaging through and within complex samples presents a significant challenge due to random light scattering, with substantial implications across multiple fields. While significant advancements in coherent imaging through severe multiple scattering have been recently introduced by reflection-matrix processing, approaches that tackle scattering in incoherent fluorescence imaging have been limited to sparse targets, require high-resolution control of the illumination or detection wavefronts, or a very large number of measurements. Here, we present an approach that allows direct application of well-established reflection-matrix techniques to scattering compensation in incoherent fluorescence imaging. We experimentally demonstrate that a small number of conventional widefield fluorescence-microscope images acquired under unknown random illuminations can effectively construct a fluorescence-based virtual reflection matrix. This matrix, when processed by conventional matrix-based scattering compensation algorithms, allows reconstructing megapixel-scale fluorescence images, without requiring the use of spatial-light modulators (SLMs) or computationally-intensive processing.","url_abs":"https://arxiv.org/abs/2312.16065v1","url_pdf":"https://arxiv.org/pdf/2312.16065v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"noninvasive-megapixel-fluorescence-microscopy","repo_url":"https://github.com/Imaging-Lab-HUJI/Fluorescence-Computational-Imaging-Through-Scattering-Layers","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}