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Updated: Jun 4, 2025

Rapid Analysis and Exploration of Fluorescence Microscopy Images
Published on: March 19, 2014
Efficiently accelerated bioimage analysis with NanoPyx, a Liquid Engine-powered Python framework
Bruno M Saraiva1,2, Inês Cunha1,3,4, António D Brito1,5
1Instituto Gulbenkian de Ciência, Oeiras, Portugal.
None:
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.
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