GitHub - crocodoyle/deep-mri-qc: This project is trained on private MRI data, where scans are marked QC_PASS or QC_FAIL. Several architectures of neural networks are explored to make automatic predictions for new images.

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This project is trained on private MRI data, where scans are marked QC_PASS or QC_FAIL. Several architectures of neural networks are explored to make automatic predictions for new images.

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Name		Name	Last commit message	Last commit date
Latest commit History 1,544 Commits
custom_loss.py		custom_loss.py
dataviz.py		dataviz.py
densenet.py		densenet.py
ibis_reader.py		ibis_reader.py
make_datasets.py		make_datasets.py
make_ibis.py		make_ibis.py
ml_experiment.py		ml_experiment.py
ndimage_aug.py		ndimage_aug.py
nyul_normalization.py		nyul_normalization.py
qc-3d.py		qc-3d.py
qc-abide-2d.py		qc-abide-2d.py
qc-ibis-2d.py		qc-ibis-2d.py
qc-ibis-dltk.py		qc-ibis-dltk.py
qc-top.py		qc-top.py
qc_pytorch_models.py		qc_pytorch_models.py
run_mriqc_docker.py		run_mriqc_docker.py
t1qc.py		t1qc.py
temp_scripts.py		temp_scripts.py
temperature_scaling.py		temperature_scaling.py
train_deepqc.py		train_deepqc.py
train_ibis_qc.py		train_ibis_qc.py
train_pytorch_mriqc.py		train_pytorch_mriqc.py
transformations.py		transformations.py
visualizations.py		visualizations.py

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This project is trained on private MRI data, where scans are marked QC_PASS or QC_FAIL. Several architectures of neural networks are explored to make automatic predictions for new images.

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