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Universal PTV:
Cutoffs are based on all patients. There are 2 groups: 90% below and 90% above.
Female low PTV burden: green
Female high PTV burden: purple
Male low PTV burden: blue
Male high PTV …
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Hello, I tried to reproduce your code, but what I predicted was a liver, not a liver tumor, why is that?
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Thanks you for your excellent works, I want to know whether this work is a equal way to augment data.
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In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and Int…
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To avoid maintaining multiple files
tutorial: https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/vista3d/vista3d_spleen_finetune.ipynb
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Dear Experts,
Congratulations and sincere thanks for releasing this extension.
I request inputs to run nnUNet models, available at https://zenodo.org/records/3734294, other than the TotalSegmen…
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Hello，developers of SelfMedMAE.
Your work is valuable enlightening me so much and I am trying to make some improvements to improve the effect on my liver tumor dataset.
Considering that my dataset h…
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Universal PTV with 90% cutoffs:
Cutoffs are based on all patients. There are 2 groups: 90% below and 90% above.
Female low PTV burden: green
Female high PTV burden: purple
Male low PTV burden: bl…
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Dear,
This is my first try with WSInfer, and I would like to ask for more features and advice on it.
The aim of the project:
(1) to identify metastasis sets, the statistics include: the numbe…
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Thanks for the great work.
You mentioned that location selection is the first step in tumor generation but I wonder where to find the code for it.
I noticed that random location is selected in `Tum…