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Project

Lattice Light Sheet Data Analysis Toolset


Award napari Plugin Accelerator

Project Summary

Lattice light sheet microscopy (LLSM) has revolutionized biomedical research, enabling researchers to examine biological mechanisms with previously unachievable levels of spatio-temporal resolution. The speed of this technique, combined with its relatively low phototoxicity, can generate terabytes of data per imaging session. A further complication of the technique is that the data must be processed after acquisition before it can be visualized or analyzed. These unavoidable challenges of LLSM require custom data handling and analysis pipelines, and a more unified approach would be desirable, particularly with commercial LLSM systems being made available and hence increasing the amount of LLSM users worldwide.

This team will adapt some of the existing Python implementations of LLSM deskewing workflows. Leveraging libraries within the Python ecosystem such as Dask, AICSImageIo, scipy and clesperanto will enable the development of a modular, extensible, interactive and easy-to-use napari plugin for handling, visualizing, interacting with, and analyzing LLSM data. This LLSM plugin will be a valuable addition to the scientific and bioimage analysis ecosystem by tackling the bottleneck of handling and processing big data in a user-friendly way. It will allow researchers to focus their time on interpreting the data and understanding the biology, thus accelerating the pace of scientific discoveries with this impactful technology.

Investigators

Principal Investigator
Lachlan Whitehead, PhD
Lachlan Whitehead, PhD
Co-Principal Investigators
Pradeep Rajasekhar, PhD
Pradeep Rajasekhar, PhD
Nina Tubau Ribera, MA
Nina Tubau Ribera, MA