Efficiently accelerated bioimage analysis with NanoPyx, a Liquid Engine-powered Python framework.
Where this comes from
- Record sourced from PubMed, PMID 39747509.
- Also identified by DOI 10.1038/s41592-024-02562-6 and PMC identifier 11810771.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
The expanding scale and complexity of microscopy image datasets require accelerated analytical workflows. NanoPyx meets this need through an adaptive framework enhanced for high-speed analysis. At the core of NanoPyx, the Liquid Engine dynamically generates optimized central processing unit and graphics processing unit code variations, learning and predicting the fastest based on input data and hardware. This data-driven optimization achieves considerably faster processing, becoming broadly relevant to reactive microscopy and computing fields requiring efficiency.
Medical subject headings
- Software
- Image Processing, Computer-Assisted
- Microscopy