DeepDeWedge is A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography.

References:

• Wiedemann, S., Heckel, R. A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography Nat Commun 15, 8255 (2024).

• DeepDeWedge Github page:
  https://github.com/MLI-lab/DeepDeWedge

• Following recent updates, multi-GPU now works with "ddw fit-model". See the output of command: ddw fit-model --help
• Currently, the refine-tomogram still only works with a single GPU.

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive --gres=gpu:p100:1,lscratch:50 --mem=16g -c8
salloc.exe: Pending job allocation 44219178
salloc.exe: job 44219178 queued and waiting for resources
salloc.exe: job 44219178 has been allocated resources
salloc.exe: Granted job allocation 44219178
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn2364 are ready for job

[user@cn2364 ~]$ module load deepdewedge
[user@cn2364 ~]$ ddw --help
[user@cn2364 ~]$ ddw prepare-data --help
[user@cn2364 ~]$ ddw fit-model --help
[user@cn2364 ~]$ ddw refine-tomogram --help