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Unsupervised Multi-scale Segmentation of Cellular cryo-electron Tomograms with Stable Diffusion Foundation Model

2025-06-28

Abstract excerpt

We introduce an unsupervised approach for segmenting multiscale subcellular objects in 3D volumetric cryo-electron tomography (cryo-ET) images, addressing key challenges such as large data volumes, low signal-to-noise ratios, and the heterogeneity of subcellular shapes and sizes. The method requires users to select a small number of slabs from a few representative tomograms in the dataset. It leverages features ex...

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Literature Corpus work
d74e6d9d-db14-5e0b-9de5-ff89edeb8e4e
DOI
10.1101/2025.06.25.661425
Open publication

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Unsupervised Multi-scale Segmentation of Cellular cryo-electron Tomograms with Stable Diffusion Foundation ModelDOI 10.1101/2025.06.25.661425
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