Visualizing & Quantifying Mesoscale Structure & Organization in Human Cells
To develop and incorporate machine learning algorithms for segmentation of cellular organelles into the soft x-ray tomography pipeline and generate images of segmented cells for the Human Cell Atlas.
Results & Resources
The Larabell lab continues development of soft X-ray tomography as an alternative to traditional tomography or EM methods that require dehydration, staining and embedding. The result is high resolution 3D images of subcellular structures. They developed machine learning methods for data binning and semantic segmentation to help with processing and annotation of structures within intact cells.