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--- |
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license: apache-2.0 |
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--- |
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# DiffTumor |
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The Singularity container is designed for the prediction of abdominal tumors, specifically targeting the liver, pancreas, and kidneys. It utilizes a segmentation model sourced from [DiffTumor](https://github.com/MrGiovanni/DiffTumor). |
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# Instructions |
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### 1-Download |
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Download the singularity container. |
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``` |
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wget https://huggingface.co/qicq1c/DiffTumor/resolve/main/difftumor_final.sif |
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``` |
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### 2-Data preparation |
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This is how `inputs_data` organizes |
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``` |
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$inputs_data/ |
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├── case00001.nii.gz |
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├── case00002.nii.gz |
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├── case00003.nii.gz |
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├── ... |
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``` |
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### 3-Inference |
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You can directly perform inference on your own data. Simply modify `inputs_data` into your data path and adjust `outputs_data` to specify the desired output location for the segmentation results. |
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``` |
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SINGULARITYENV_CUDA_VISIBLE_DEVICES=0 singularity run --nv -B $inputs_data:/workspace/inputs -B $outputs_data:/workspace/outputs difftumor_final.sif |
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``` |
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This is how `outputs_data` organizes |
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``` |
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$outputs_data/ |
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├── case00001 |
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├── case00002 |
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├── case00003 |
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│── ct.nii.gz |
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└── predictions |
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├── liver.nii.gz |
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├── pancreas.nii.gz |
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├── kidney.nii.gz |
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├── liver_tumor.nii.gz |
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├── pancreas_tumor.nii.gz |
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├── kidney_tumor.nii.gz |
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│ |
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... |
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``` |
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