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linyebin123 b0128b7bed | 1 year ago | |
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.. | ||
README.md | 1 year ago | |
brats_config.json | 1 year ago | |
brats_subjects_2020.json | 1 year ago |
git clone https://github.com/ellisdg/3DUnetCNN.git
cd 3DUnetCNN
export PYTHONPATH=${PWD}:${PYTHONPATH}
cd
into the brats2020
example directory:cd examples/brats2020
brats2020
example directory.MICCAI_BraTS2020_TrainingData
MICCAI_BraTS2020_ValidationData
.python ../../unet3d/scripts/train.py --config_filename ./brats_config.json --model_filename ./brats_unet3d_baseline.h5 --training_log_filename brats_baseline_training_log.csv --nthreads <nthreads> --ngpus <ngpus> --fit_gpu_mem <gpu_mem>
<nthreads>
,
<ngpus>
, and
<gpu_mem>
should be set to the number of threads, number of GPUs, and the amount of GPU memory in GB on a single gpu that will be used for training.
python ../../unet3d/scripts/predict.py --segment --output_directory ./predictions/validation/baseline --config_filename ./brats_config_auto.json --model_filename ./brats_unet3d_baseline.h5 --replace Training Validation --group validation --output_template "BraTS20_Validation_{subject}.nii.gz" --nthreads <nthreads> --ngpus <ngpus>
<nthreads>
and
<ngpus>
should be set to the number of threads and gpus that you are using.
The predicted tumor label map volumes will be in the folder: ./predictions/validation/baseline
These label maps are ready to be submitted to the CBICA portal
that the BraTS challenge uses to score and rank submissions.
The train.py
script will automatically set the input image size and batch size based on the amount of GPU memory and number of GPUs.
If you do not want these settings automatically set, you can adjust them yourself by making changes to the config file instead of using the
--fit_gpu_mem
flag.
Rather than specifying the number of GPUs and threads on the command line, you can also make a configuration file for the machine you are using
and pass this using the --machine_config_filename
flag.
Click here to see an example machine configuration JSON file.
用于医学图像分割的Pytorch 3D U-Net卷积神经网络(CNN)
Python
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