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Comments (7)

Meddebma avatar Meddebma commented on June 2, 2024

Thank you so much for this code, it worked really well. I am impressed with the quality!

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louisblankemeier avatar louisblankemeier commented on June 2, 2024

Hi @Meddebma,

Did you get the code running on google colab? I haven't tried this so curious if it worked for you. Thank you!

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louisblankemeier avatar louisblankemeier commented on June 2, 2024

Also, we have a function that supports nifti inputs here https://github.com/StanfordMIMI/Comp2Comp/blob/master/comp2comp/io/io_utils.py#L31 but have not yet tested this extensively as a part of the pipelines. We will at this to our todos. We do not currently support nifti outputs, besides the segmentation files which are stored as niftis.

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Meddebma avatar Meddebma commented on June 2, 2024

Hi @louisblankemeier ,

yes it worked perfectly, here is the code:
!git clone https://github.com/StanfordMIMI/Comp2Comp/ %cd Comp2Comp !pip install -e . !bin/C2C spine_muscle_adipose_tissue --input_path /content/drive/MyDrive/CT_body_comp_AI/example/sr
It took 90-120sec per CT scan.
I am really impressed how good it is!
Definitely gonna use it for my next research

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louisblankemeier avatar louisblankemeier commented on June 2, 2024

I'm glad it worked for you on colab, that's really good to know!!

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akshaysc avatar akshaysc commented on June 2, 2024

Maybe a Colab version is something we post on the repo as an example use case? Perhaps with voxel integration for viewing?

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louisblankemeier avatar louisblankemeier commented on June 2, 2024

Agreed!! I think we've surfaced several cases where people would want to interact with outputs in python (going beyond the CL interface) and a colab tutorial would be well suited here. As you mentioned, one case is visualizing outputs for development and QA, and voxel would be perfect for that! I think we should add this to the top of our TODOs.

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