ArticleChemical & biomedical imaging2025
D‑Blur: A Deep Learning Approach for Mapping Subdiffraction Diffusion with Motion-Blurred Images.
Article in Chemical & biomedical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Image-based single-particle tracking (SPT) provides insight into complex transport within diverse biological and porous material structures, but its performance is constrained by motion blur and a low signal-to-noise ratio (SNR). Traditional SPT methods are sensitive to localization errors and often struggle with short trajectories and fast-moving emitters. In this work, we develop D-Blur, a U-Net-based convolutional neural network (CNN) algorithm designed to localize single particles and predict their diffusion coefficients (
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