henhaobio
Sign in

bioRxivBioinformaticsPreprint

A real-time compression library for microscopy images

Bálint BalázsiD, J.R. DeschampsiD, Marvin AlbertiD, Jonas RiesiD, Lars HufnageliD

PDFDOI

Abstract

Fluorescence imaging techniques such as single molecule localization microscopy, high-content screening and light-sheet microscopy are producing ever-larger datasets, which poses increasing challenges in data handling and data sharing. Here, we introduce a real-time compression library that allows for very fast (beyond 1 GB/s) compression and de-compression of microscopy datasets during acquisition. In addition to an efficient lossless mode, our algorithm also includes a lossy option, which limits pixel deviations to the intrinsic noise level of the image and yields compression ratio of up to 100-fold. We present a detailed performance analysis of the different compression modes for various biological samples and imaging modalities.

Citations
30

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISWalker '23Duan '24Ma '20Collard '26Woringer '17Cheeseman '18
79% semantic matchBioinformatics
Logan A. Walker, Ye Li, Maggie Mcglothlin+1 more·International Conference on Software Engineering and Information Management (ICSIM)·Jan 31, 2023· 4 citations