Related Experiment Video
Updated: Feb 5, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
Published on: November 11, 2022
CDeep3M-Plug-and-Play cloud-based deep learning for image segmentation
Matthias G Haberl1,2, Christopher Churas3, Lucas Tindall4
1National Center for Microscopy and Imaging Research, School of Medicine, University of California San Diego, La Jolla, CA, USA. haberlmatt@gmail.com.
Abstract:
As biomedical imaging datasets expand, deep neural networks are considered vital for image processing, yet community access is still limited by setting up complex computational environments and availability of high-performance computing resources. We address these bottlenecks with CDeep3M, a ready-to-use image segmentation solution employing a cloud-based deep convolutional neural network. We benchmark CDeep3M on large and complex two-dimensional and three-dimensional imaging datasets from light, X-ray, and electron microscopy.
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