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UID:pretalx-scipy-2026-TADDJP@pretalx.com
DTSTART;TZID=CST:20260715T104500
DTEND;TZID=CST:20260715T111500
DESCRIPTION:Bioimaging generates massive datasets in fragmented\, proprieta
 ry formats that are difficult to share and align with FAIR principles. ngf
 f-zarr is a lightweight\, open-source Python toolkit implementing the OME-
 Zarr specification -- the community-driven\, cloud-native bioimaging stand
 ard. With minimal dependencies and a simple pipeline interface\, ngff-zarr
  converts\, validates\, and generates multiscale representations of extrem
 ely large images out-of-core via Dask. Features include multiple downscali
 ng methods\, OME-Zarr Zip archives (.ozx)\, RFC-4 anatomical orientation\,
  and High Content Screening support. This talk also covers ngff-zarr's Mod
 el Context Protocol (MCP) server\, which enables AI agents to perform bioi
 maging tasks through natural language\, and lessons learned from its deplo
 yment at EMBL.
DTSTAMP:20260715T021156Z
LOCATION:University Hall
SUMMARY:A Lean and Kind OME-Zarr Toolkit for Bioimaging - Matt McCormick
URL:https://pretalx.com/scipy-2026/talk/TADDJP/
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