3DM: Deep decomposition and deconvolution microscopy

Demo video acquired using 3DM.

Compression is applied. Supplementary video 1 is the video before compression.

Paper

Official source codes for "3DM: Deep decomposition and deconvolution microscopy", Optics Express.

ABSTRACT

Requirements

python==3.7.6
torch==1.5.0
skimage==0.16.2

Demo: BEAR + Deconvolution with pretrained weight

./run_jupyter.sh

This notebook lets you:

• Download a portion (t=1~50, size=TODO) of calcium imaging data acquired with our wide-field microscope.
• Do unsupervised low rank and sparse decomposition using BEAR.
• Load the pretrained 3-D deconvolution network.
• Do deconvolution for each 50 sparse volumes.
• Visualize the results.

Train

The following command starts training the 3-D deconvolution network:

python codes/train.py

Test

The following commands do deconvolution after loading the pretrained weight.

python codes/eval_simulation.py --exp_name 3DM --epoch 26000
python codes/eval_3DM_video.py --exp_name 3DM --epoch 26000

• eval_simulation.py do deconvolution for simulated wide-field data. (See Section 3.1)
• eval_3DM_video.py do deconvolution for wide-field data acquired with our microscope. (See Section 3.2)

Citation

TODO

@article{cho2021deep,
  title={3DM: Deep decomposition and deconvolution microscopy},
}