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Submission for Multimodal Brain Tumor Segmentation Challenge 2017 (http://braintumorsegmentation.org/). A patch-based 3D U-Net model is used. Instead of predicting the class label of the center pixel, this model predicts the class label for the entire patch. A sliding-window method is used in deployment with overlaps between patches to average the predictions.
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The workflow includes bias correction, patch extraction, training, post-processing, testing and submission.
After training data is downloaded, run python bias_correction.py input_dir to perform bias field correction based on N4ITK (https://www.ncbi.nlm.nih.gov/pubmed/20378467). The corrected dataset will be saved at the same folder with the raw dataset.Run python generate_patches.py input_dir output_dir to generate patches for training.To train the model, run python main.py --train=True --train_data_dir=train_patch_dir . Or you can modify the default parameters in main.py so that you can just run python main.py . Check model.py for more details about the network structure.To test the model on validation dataset, run python main.py --train=False --deploy_data_dir=deploy_data_dir --deploy_output_dir=deploy_output_dir . The results will be saved at deploy_output_dir . The network structure for survival prediction is not working good as the result is similar as random guessing. So you can ignore that by setting run_survival to False .To combine the results and generate the final label maps, run python prepare_for_submission.py input_dir output_dir .
Installation
The model is implemented and tested using
python 2.7 and Tensorflow 1.1.0 , but python 3 and newer versions of Tensorflow should also work.Other required libraries include: numpy , h5py , skimage , transforms3d , nibabel , scipy , nipype . You also need to install ants Hp color laserjet 2840 driver windows 7 64 bit download. for bias correction. Read the instructions for Nipype (http://nipy.org/nipype/0.9.2/interfaces/generated/nipype.interfaces.ants.segmentation.html) and Ants (http://stnava.github.io/ANTs/) for more information.
ContributorsGithub Commit To Master
Xue Feng, Department of Biomedical Engineering, University of [email protected]
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