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Hello,
thank you for uploading the project!
As I would like to reproduce the results in your paper I would like to use the same pre-processing pipeline.
Could you upload the code for processing…
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I am trying to run the hyperparameters search on EBM and using the hyperopt but I have noticed each iteration will increase the memory usage and wondering if there is a way to clear the memory usage o…
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The current implementation only supports one type of normalization for a whole input series. In some cases, you might want different normalization applied to individual input images or no normalizatio…
che85 updated
6 months ago
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Hello, author, I run according to your test.py. The following problems occur. What is the reason? We look forward to you.
Working with 1 GPUs
invalid literal for int() with base 10: ''
using defa…
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Hello,
I'm trying this amazing work! Thanks for your contributions.
I want to train a model on MSD 001 brain tumor dataset, but I only interests in contrast-enhanced tumor and T1c modality. How t…
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Hey !!
i have run the code with BraTS2018 dataset, the dice score is low than you claimed, i will attach the picture for reference.
The dice score that you have claimed (T2-T1) is 0.6793 …
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Hi, when executing the following transforms, I get this error
train_transform = Compose(
[
AddChanneld(keys=["image", "label"]),
Spacingd(keys=['image', 'label'], pixdim=(1…
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Hi, Thank you for your reply. I have one more question related to configurations. Can you elaborate a bit on " --json_file JSON_FILE path to json file". What kind of data does it contain? Is it the fo…
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First of all, thank you for your effort. I'm a 5th-year medicine student, and nnUNet has helped me a lot on several of my projects.
I'm trying to utilize nnUNet for a case where I have five differe…
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Hello, I have trained the forward diffusion model by "python modality_cyclic_train.py --input flair --trans t1 --model_name diffusion " and backward model by "python modality_cyclic_train.py --input …