Adaptive particle representation of fluorescence microscopy images

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

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.

Details

Original languageEnglish
Article number5160
JournalNature Communications
Volume9
Issue number1
Publication statusPublished - 1 Dec 2018
Peer-reviewedYes

External IDs

Scopus 85057599428
ORCID /0000-0003-4414-4340/work/142252130

Keywords