Efficiently accelerated bioimage analysis with NanoPyx, a Liquid Engine-powered Python framework.

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Saraiva BM, Cunha I, Brito AD, Follain G, Portela R, Haase R, Pereira PM, Jacquemet G, Henriques R

Nat. Methods 22 (2) 283-286 [2025-02-00; online 2025-01-02]

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.

PubMed 39747509

DOI 10.1038/s41592-024-02562-6

Crossref 10.1038/s41592-024-02562-6

pmc: PMC11810771
pii: 10.1038/s41592-024-02562-6