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Large Scale Registration


Tutorial Description

Lightsheet microscopy methods for mouse brains result in volumes that are not feasible to register at full resolution on a standard single computer. As we move to register rats, non-human primates and whole human brains, a scalable registration approach is required that is not limited by the memory capacity of modern computational nodes and the computational capability of a single system.

In this tutorial, we will cover principles for large scale registration that combine the OME-Zarr NGFF, Xarray, and Dask, a distributed computing library for Python, to register neuroimages in a way that can limit memory consumption, distribute computation, and perform a coarse-to-fine registration that progressively aligns structures across multiple scales.

Duration: 0.5 hours.

Learning Outcomes

  1. Outcome 1. Understand the need for multiscale OME-Zarr spatial metadata and how to generate this metadata.
  2. Outcome 2. Learn how to distribute registration to limit memory consumption and improve performance.

Approach and Materials

Background and References