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Automated Multimodal Image Registration in napari

Award napari Plugin Accelerator

Project Summary

This project aims to bring an automated whole slide image (WSI) registration plugin into the napari ecosystem. Many tasks such as WSI segmentation and registration heavily rely on Python code, especially in deep learning. With the creation of napari, visualization within Python of multi-scale data has been greatly improved. This mitigates patchwork workflows incorporating different software, programming languages, and web applications that may intimidate novice programmers and scientist users.

Creating tools that unify WSI analysis and visualization in Python is now possible in napari and therefore timely and critically important. The software for translation in this proposal, wsireg, is an elastix-based WSI registration framework using a graph to smartly connect images (nodes) for registration (edges). wsireg fits within this ecosystem by providing a powerful toolbox for registration of different WSIs for multimodal image analysis.

By creating a napari plugin called napari-wsireg, users will have an intuitive interface to set up, perform, and evaluate complex registrations between multiple WSIs and their associated data, ultimately facilitating more complex image study designs and analyses that can answer difficult clinical or biological questions.


Principal Investigator
Heath Patterson, PhD
Heath Patterson, PhD