msseg_snac_gpu.json

{
    "name": "MSSeg_SNAC_Method_GPU",
    "description": "Detect new MS lesions from two FLAIR images using a CNN and attention.",
    "author": "Mariano Cabezas",
    "tool-version": "v0.1.0",
    "schema-version": "0.5",
    "command-line": "python /src/inference.py -t1 [FLAIR1] -t2 [FLAIR2] -o [SEGMENTATION]",
    "container-image": {
        "image": "mcabezas/msseg_snac:v1.0.0",
        "index": "hub.docker.com",
        "type": "docker",
        "container-opts": [
            "--gpus",
            "all"
        ]

    },
    "inputs": [
        {
            "id": "flair_time01",
            "name": "The first flair image (e.g. flair_time01.nii.gz)",
            "optional": false,
            "type": "File",
            "value-key": "[FLAIR1]"
        },
        {
            "id": "flair_time02",
            "name": "The second flair image (e.g. flair_time02.nii.gz)",
            "optional": false,
            "type": "File",
            "value-key": "[FLAIR2]"
        },
        {
            "id": "output_segmentation",
            "name": "The output segmentation (e.g. segmentation.nii.gz)",
            "optional": false,
            "type": "String",
            "value-key": "[SEGMENTATION]"
        }
    ],
    "output-files": [
        {
            "id": "segmentation",
            "name": "The segmentation output",
            "optional": false,
            "path-template": "[SEGMENTATION]"
        }
    ]
}