Electron Tomography
10 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Electron Tomography
Most implemented papers
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images
In cryo-electron microscopy (EM), molecular structures are determined from large numbers of projection images of individual particles.
AITom: Open-source AI platform for cryo-electron tomography data analysis
xulabs/aitom
•
•
Cryo-electron tomography (cryo-ET) is an emerging technology for the 3D visualization of structural organizations and interactions of subcellular components at near-native state and sub-molecular resolution.
Shape from Projections via Differentiable Forward Projector for Computed Tomography
jakeoung/ShapeFromProjections
•
•
In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization.
Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration From Single Noisy Volume With Sparsity Constraint
The proposed method only requires a single noisy data as training input and no ground-truth is needed in the whole training procedure.
Statistical spatial analysis for cryo-electron tomography
Here, we designed and implemented first and the second-order, uni- and bivariate PPA functions in a Python package for statistical spatial analysis of particles located in three dimensional regions of arbitrary shape, such as those encountered in cellular cryo-ET imaging (PyOrg).
Boosting Active Learning via Improving Test Performance
xulabs/aitom
•
•
In this work, we explore such an impact by theoretically proving that selecting unlabeled data of higher gradient norm leads to a lower upper-bound of test loss, resulting in better test performance.
Deep learning-based identification of sub-nuclear structures in FIB-SEM images
Lastly, we highlight specific aspects of the model that can be optimized for its broad application to other volumetric imaging data as well as in situ cryo-electron tomography.
Real-Time Tilt Undersampling Optimization during Electron Tomography of Beam Sensitive Samples using Golden Ratio Scanning and RECAST3D
Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples.
A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography
At the same time, DeepDeWedge is simpler than this two-step approach, as it does denoising and missing wedge reconstruction simultaneously rather than sequentially.
Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation
swing-research/implicit-cryo-electron-tomography
•
•
We introduce ICE-TIDE, a method for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume.
