Abstract
High-density analysis methods for localization microscopy increase acquisition speed but produce artifacts. We demonstrate that these artifacts can be eliminated by the combination of Haar wavelet kernel (HAWK) analysis with standard single-frame fitting. We tested the performance of this method on synthetic, fixed-cell, and live-cell data, and found that HAWK preprocessing yielded reconstructions that reflected the structure of the sample, thus enabling high-speed, artifact-free super-resolution imaging of live cells.
Original language | English |
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Pages (from-to) | 689-692 |
Journal | NATURE METHODS |
Volume | 15 |
Early online date | 30 Jul 2018 |
DOIs | |
Publication status | Published - Sept 2018 |
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Raw data for HAWK paper
Marsh, R., Pfisterer, K., Bennett, P., Hirvonen, L., Gautel, M., Jones, G. E. & Cox, S., King's College London, 5 Jun 2018
DOI: 10.18742/RDM01-318, https://kcl.figshare.com/articles/dataset/Raw_data_for_HAWK_paper/16473801
Dataset