3DUnetCNN
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I'm really sorry for bothering you.
I'm really sorry for bothering you. Your code is designed for four channels, but I only need one channel for my application. I have already changed the number of channels. Could you please let me know what other parts I need to modify?
If you haven't already, checkout BraTS example notebook for an explanation of the different arguments: https://github.com/ellisdg/3DUnetCNN/blob/master/examples/brats2020/create_config_lowmem.ipynb
Some arguments you may consider changing:
- "desired_shape"
- "setup_label_hierarchy" should be false since you only have a mask as output based on your previous comment
- "resample" and "crop_foreground" may not be necessary depending on the images and image sizes in your dataset.
I'm really sorry for bothering you,I'm using it to train in my own dataset.Discovering these images in the example folder after training, does it mean that the training was successful?"If it is successful, how should I run the predict.py file?
Those are 3D renderings that I made as an example of skull completion using the AutoImplant dataset.
You should have a training log file that you can look at to see how many epochs were run and if the training and validation losses decreased like you would expect.