ArticleNature communications2018
Adaptive particle representation of fluorescence microscopy images.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Visualizing the multidimensional landscape of biological variation in modern microscopy.Frontiers in bioinformatics · 2026Article
- Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy.Patterns (New York, N.Y.) · 2025Review
- Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level.Neuroscience bulletin · 2023Review
- Maximized Spatial Information and Minimized Acquisition Time of Top-Hat IR-MALDESI-MSI of Zebrafish Using Nested Regions of Interest (nROIs).Journal of the American Society for Mass Spectrometry · 2023Article
- It's clearly the heart! Optical transparency, cardiac tissue imaging, and computer modelling.Progress in biophysics and molecular biology · 2022Article
- Developing open-source software for bioimage analysis: opportunities and challenges.F1000Research · 2021Article
- Tissue clearing and its applications in neuroscience.Nature reviews. Neuroscience · 2020Review
- Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafish.Nature communications · 2019Article
- 4D cell biology: big data image analytics and lattice light-sheet imaging reveal dynamics of clathrin-mediated endocytosis in stem cell-derived intestinal organoids.Molecular biology of the cell · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern microscopes create a data deluge with gigabytes of data generated each second, and terabytes per day. Storing and processing this data is a severe bottleneck, not fully alleviated by data compression. We argue that this is because images are processed as grids of pixels. To address this, we propose a content-adaptive representation of fluorescence microscopy images, the Adaptive Particle Representation (APR). The APR replaces pixels with particles positioned according to image content. The APR overcomes storage bottlenecks, as data compression does, but additionally overcomes memory and processing bottlenecks. Using noisy 3D images, we show that the APR adaptively represents the content of an image while maintaining image quality and that it enables orders of magnitude benefits across a range of image processing tasks. The APR provides a simple and efficient content-aware representation of fluosrescence microscopy images.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.