Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 57,915 bioRxiv papers from 266,490 authors.
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.
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