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Project

Improving Image Processing


Award napari Plugin Accelerator

Project Summary

The napari-pyclesperanto-assistant is the only existing napari plugin for general purpose image processing. It offers functionality for image filtering (denoising, background subtraction), segmentation, labeling, image transformation, projections, and quantitative image analysis in the form of tabular data and parametric images. Even though deep learning has revolutionised the bioimage analysis field, particularly in the context of image denoising and segmentation, general purpose image processing is still necessary in virtually all projects involving real user scenarios in biology, medicine and biophysics. The napari-pyclesperanto-assistant allows end-users to explore image processing operations in a straightforward fashion without the need for technical implementation details and coding experience. The plugin also enables the end-users to leverage the enhanced computing power of graphics processing units (GPUs) without the need to learn a GPU-specific programming language.

The team will extend the napari plugin to incorporate functionalities that already exist on ImageJ/Fiji, namely undo features. The napari-pyclesperanto-assistant stores an image data flow graph, a lightweight version of an image processing workflow that can be updated whenever the user changes it. This will enable the user to undo previous operations, enabling exploratory analysis with almost real-time feedback. This feature will increase the throughput and accuracy when developing bioimage analysis pipelines. The team will continue close collaboration with the napari community with input from the core developers, and shape new tools for the life sciences community.

Investigators

Principal Investigator
Robert Haase, PhD
Robert Haase, PhD
Co-Principal Investigators
Lachlan Whitehead, PhD
Lachlan Whitehead, PhD