3260 papers • 126 benchmarks • 313 datasets
Cryogenic Electron Tomography
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These leaderboards are used to track progress in cryogenic-electron-tomography-1
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Use these libraries to find cryogenic-electron-tomography-1 models and implementations
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A deep-learning approach for simultaneous denoising and missing wedge reconstruction called DeepDeWedge, which is simpler than current state-of-the-art approaches for denoising and missing wedge reconstruction, performs competitively and produces more denoised tomograms with higher overall contrast.
ICE-TIDE, a method for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume, relies on an efficient coordinate-based implicit neural representation of the volume which enables it to directly parameterize deformations and align the projections.
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