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Thank you very much for your contribution to medical segmentation! To make it easier to follow your work, could you provide a list of specific training, validation and test set documents?
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### UNN_BraTS23/scripts/data_class.py
**lines: 41-69**
Should this section not account for when mask does not exist?
_see code change suggestion in docstring at end_
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Hi, when using openmap t1 for segmentation with Brain tumor data there are so many empty regions in the output. How to overcome this? Are there any special preprocessing tasks to deal with tumor datas…
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Hi, thank you for publishing your code.
I am having trouble reproducing your results reported in the paper by training my own model using 5-fold cross-validation. I am using batch size 1 and the v…
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Hi @TaWald,
I would like to check which information was crucial to replicate lesion-wise evaluation which is used for HD-BM paper.
What I have found in the supplement document is the following:
…
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The predictions have size 256x256x1. However, my input images have dimensions 256x256x256. Is this normal? And if not, how do I tweak the code so has to have same dimension output as my input?
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initial lr is 0.01
scheduler_type is poly, warmup steps is 0
Epoch 0: 0%| …
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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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Hi @MrGiovanni,
Thank you for open-sourcing all the models and weights from this very insightful study.
I'm comparing some of our trained SegResNet architectures against the SuPreM SegResNet. …
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how to train a model?