ArticleBiophysical journal2017
Quantitative Image Restoration in Bright Field Optical Microscopy.
Article in Biophysical journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Making sense of blobs, whorls, and shades: methods for label-free, inverse imaging in bright-field optical microscopy.Biophysical reviews · 2025Review
- Quantification of bacterial shape using moment invariants enables distinguishing populations during cellular plasmolysis.MethodsX · 2024Article
- Optical sectioning of unlabeled samples using bright-field microscopy.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis.
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