zhiyuns / AFCM

Official PyTroch implementation of the MICCAI 2023 paper "Alias-Free Co-Modulated Network for Cross-Modality Synthesis and Super-Resolution of MR Images"
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About code #1

Closed zwq1111 closed 10 months ago

zwq1111 commented 11 months ago

Thanks for the code you provided. But I meet some problems when I run the code, I want to know whether the code is entire or not. If it is entire, I am so sorry to bother you. If it is not, I would like you to post the complete code. Thank you very much again!

zhiyuns commented 11 months ago

We are sorry for the potential problems with the SR experiments and update the code to fix them. Please feel free to contact us if you have further questions.

zwq1111 commented 11 months ago

Thank you very much for your reply! I have another question, I noticed that you have processed the dataset used accordingly when running the code. I am currently looking into this part and I was wondering if it would be possible to tell me how the dataset was processed.

zhiyuns commented 11 months ago

As described by the paper, when performing cross-modality synthesis, we first co-registrate the modalities using ANTsPy ( mode) and then prepare the h5 file using ./data/prepare_h5.py. If you want to perform super-resolution, please resample the HR image to get LR image, and upsample the LR image using to match the shape with HR image. After that, prepare the h5 file using ./data/prepare_h5.py. We also upload an example as ./data/ixi_demo.h5 for a clearer demonstration of this process.

zwq1111 commented 11 months ago

Thanks again for your reply! I have one more question about the code. I have downloaded the required ixi dataset on the website, but I didn't find the 'T1_HR' and 'T2_FLAIR_linear' modality data in ./data/prepare_h5.py. I'd like to ask you for details about it. code

zhiyuns commented 11 months ago

It's just an example, you can modify it to fit the actual task and situation. For IXI, you can modify it with ['T1', 'T2', 'PD'] to reproduce our result.