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a , Scalability of SALM across optical and ultrasound modalities. b , Conventional localization microscopy mechanism <t>requires</t> <t>high-speed</t> acquisition to freeze motion for accurate tracking. c , SALM leverages motion-blurred streaks as signal carriers, eliminating the need for explicit localization and tracking via LTf-Net. d , Three illumination modes for optical-SALM embed vectorial flow information (velocity and direction) into each streak. e , Spatiotemporal graph-based simulation engine generates realistic paired datasets for network training.
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a , Scalability of SALM across optical and ultrasound modalities. b , Conventional localization microscopy mechanism <t>requires</t> <t>high-speed</t> acquisition to freeze motion for accurate tracking. c , SALM leverages motion-blurred streaks as signal carriers, eliminating the need for explicit localization and tracking via LTf-Net. d , Three illumination modes for optical-SALM embed vectorial flow information (velocity and direction) into each streak. e , Spatiotemporal graph-based simulation engine generates realistic paired datasets for network training.
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a , Scalability of SALM across optical and ultrasound modalities. b , Conventional localization microscopy mechanism <t>requires</t> <t>high-speed</t> acquisition to freeze motion for accurate tracking. c , SALM leverages motion-blurred streaks as signal carriers, eliminating the need for explicit localization and tracking via LTf-Net. d , Three illumination modes for optical-SALM embed vectorial flow information (velocity and direction) into each streak. e , Spatiotemporal graph-based simulation engine generates realistic paired datasets for network training.
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a , Scalability of SALM across optical and ultrasound modalities. b , Conventional localization microscopy mechanism requires high-speed acquisition to freeze motion for accurate tracking. c , SALM leverages motion-blurred streaks as signal carriers, eliminating the need for explicit localization and tracking via LTf-Net. d , Three illumination modes for optical-SALM embed vectorial flow information (velocity and direction) into each streak. e , Spatiotemporal graph-based simulation engine generates realistic paired datasets for network training.

Journal: bioRxiv

Article Title: Streak-Aware Localization Microscopy Enables High-Throughput Brain Imaging Across Platforms

doi: 10.64898/2026.03.04.709480

Figure Lengend Snippet: a , Scalability of SALM across optical and ultrasound modalities. b , Conventional localization microscopy mechanism requires high-speed acquisition to freeze motion for accurate tracking. c , SALM leverages motion-blurred streaks as signal carriers, eliminating the need for explicit localization and tracking via LTf-Net. d , Three illumination modes for optical-SALM embed vectorial flow information (velocity and direction) into each streak. e , Spatiotemporal graph-based simulation engine generates realistic paired datasets for network training.

Article Snippet: Optical system validation was performed using data acquired from a high-speed camera (pco.dimax S1, PCO AG, Germany).

Techniques: Microscopy