ACE-HetEM for ab initio Heterogenous Cryo-EM 3D Reconstruction. (arXiv:2308.04956v1 [eess.IV])

Due to the extremely low signal-to-noise ratio (SNR) and unknown poses
(projection angles and image translation) in cryo-EM experiments,
reconstructing 3D structures from 2D images is very challenging. On top of
these challenges, heterogeneous cryo-EM reconstruction also has an additional
requirement: conformation classification. An emerging solution to this problem
is called amortized inference, implemented using the autoencoder architecture
or its variants. Instead of searching for the correct
image-to-pose/conformation mapping for every image in the dataset as in
non-amortized methods, amortized …

3d reconstruction arxiv challenges classification cryo-em image images low noise projection signal solution translation