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Deep Learning-Based Segmentation for Bright Field Images

Award napari Plugin Foundation

Project Summary

Image segmentation is a fundamental step of microscopy image analysis, and many segmentation methods specialize in segmenting fluorescence images, some of which are available via napari. However, fluorescence imaging for image segmentation adds little biological information and is toxic to live cells. In contrast, bright field imaging is less phototoxic and captures diverse biological information. Deep learning provides powerful solutions to the challenges of bright field image segmentation, yet the necessary coding abilities limit widespread use.

The aim of this plugin is to provide user-friendly access to deep learning-based bright field image segmentation in napari.


Principal Investigator
Timm Schroeder, PhD
Timm Schroeder, PhD
Co-Principal Investigator
Daniel Schrimacher, MSc
Daniel Schrimacher, MSc