Jordão Bragantini
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Sessions
Between telescopes and satellite cameras and MRI machines and microscopes, scientists are producing more images than they can realistically look at. They need specialized viewers for multi-dimensional images, and automated tools to help process those images into knowledge. In this tutorial, we will cover the fundamentals of algorithmic image analysis, starting with how to think of images as NumPy arrays, moving on to basic image filtering, and finishing with a complete workflow: segmenting a 3D image into regions and making measurements on those regions. At every step, we will visualize and understand our work using matplotlib and napari.
Accurate cell tracking is essential to various biological studies. In this talk, we present Ultrack, a novel Python package for cell tracking that considers a set of multiple segmentation hypotheses and picks the segments that are most consistent over time, making it less susceptible to mistakes when traditional segmentation fails.
The package supports various imaging modalities, from small 2D videos to terabyte-scale 3D time-lapses or multicolored datasets in any napari-compatible image format (e.g. tif, zarr, czi, etc.).
It is available at https://github.com/royerlab/ultrack