Preprocessing for MRI data

[HongxiY]

Hello, I attempted to implement your pre-trained model on the BraTS dataset (and thank you for your previous response). However, I'm facing challenges in replicating the results outlined in your paper. I'm curious if you have any plans to share the code or supplementary materials for working with the BraTS dataset?

Alternatively, could you offer some insights into your preprocessing steps for BraTS data using MONAI, particularly focusing on data transformation and augmentation techniques? Since MRI data differs from CT scans in various aspects, such as intensity, I assume that different transformations might be necessary for BraTS.

Any details you can provide would be greatly appreciated, as it would help me follow your work more effectively.

[Luffy03]

Hi, many thanks for your kind attention to our work!
Yes, you are right. We also find that the MONAI pre-processing is not very flexible for MRI data. Thus, in our experiments, we combine the MONAI and nnunet framework for all of the experiments of MRI. If you are familiar with the nnunet framework, I think it is easy to use a trainer.py file for training.
If you have difficulty with it, I will try my best to release the nnunet finetuning codes recently. However, since we conduct a few more MRI experiments in the extension, the codes may not be well-checked. Please stay tuned

[HongxiY]

Thank you very much for sharing this information. Utilizing the nnunet framework is a brilliant idea. Am I correct in understanding that you're employing nnunet for preprocessing (and possibly also post-processing) of MRI data, and adapting the U-Net backbone to transformers or other architeture?

Once again, I appreciate your efforts in sharing the code, and I'll continue to stay updated.

[Luffy03]

Thank you very much for sharing this information. Utilizing the nnunet framework is a brilliant idea. Am I correct in understanding that you're employing nnunet for preprocessing (and possibly also post-processing) of MRI data, and adapting the U-Net backbone to transformers or other architeture?

Once again, I appreciate your efforts in sharing the code, and I'll continue to stay updated.

Yes, you are right! We find that nnunet pre-processing is better for MRI. But for CT, I think the monai implementation is enough.
I suppose that I can update the codes this weekend.

[HongxiY]

Thanks a lot. I will close this issue accordingly.
Looking forward to seeing your code.

[Luffy03]

Dear researchers, our work is now available at Large-Scale-Medical, if you are still interested in this topic. Thank you very much for your attention to our work, it does encourage me a lot!