Multi Scale Texture Loss Function for CT denoising with GANs

Overall framework of MSTLF. (a) MSTLF mainly includes two essential components, i.e., Multi-Scale Texture Extractor (MSTE) and Aggregation Module (AM). (b) MSTE module and (c) dynamic aggregation by self attention mechanism.

Name		Name	Last commit message	Last commit date
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.idea		.idea
data		data
datasets		datasets
dnnlib		dnnlib
docs		docs
loss_functions		loss_functions
metrics		metrics
models		models
options		options
scripts		scripts
torch_utils		torch_utils
util		util
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
SRGAN_main.py		SRGAN_main.py
autoencoder.bash		autoencoder.bash
autoencoder_main.py		autoencoder_main.py
create_csv.py		create_csv.py
cycleGAN_test.bash		cycleGAN_test.bash
dummy_network.py		dummy_network.py
figures.py		figures.py
figures_survey.py		figures_survey.py
haralicks.json		haralicks.json
haralicks.py		haralicks.py
net_class.py		net_class.py
pix2pix_model.py		pix2pix_model.py
pix2pix_test.bash		pix2pix_test.bash
pyvenv.cfg		pyvenv.cfg
redcnn_main.py		redcnn_main.py
requirements.txt		requirements.txt
standard_GAN_main.py		standard_GAN_main.py
starGAN_main.py		starGAN_main.py
starGAN_test.py		starGAN_test.py
template_matching.py		template_matching.py
test.py		test.py
test_fid.py		test_fid.py
times.py		times.py
train.py		train.py
unit_main.py		unit_main.py
unit_main_std.py		unit_main_std.py
unit_test.bash		unit_test.bash
unit_test.py		unit_test.py

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FrancescoDiFeola/DenoTextureLoss

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Multi Scale Texture Loss Function for CT denoising with GANs

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