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Deep learning-based convolutional neural network for contrast-enhanced MR image synthesis

Python 100.00%
deep-learning image-synthesis image-translation mri-images radiation-oncology radiotherapy unet computed-tomography mri medical-imaging

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dense-dilated-residual-convolutions-for-contrast-enhanced-mri-synthesis's Issues

Poor prediction results and no pretrained model

Thanks for your excellent work! I am trying to reproduce the result. And I found that there are a pretrained model loading process. The upload repository didn't contain it. So I annotated these code and run the model. And I'm using the same BRATS2021 dataset. But the results is very poor, and different from the papaer result. The prediction result shows as below, The prediction is pretty white and differs greatly from the true value.
4434483240e9f1c11c5288a51df34c8

The training process and loss curve are list below:

9b3fe43d14d6ab2d72a3a2a292380da 9c055a8c9b6dc06d03e315733dfecac

Why this happen? How could I reproduce the paper result performance? It will be very grateful that if you could help me solve this problem.

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