Model Integration Request for medigan: 00023_PIX2PIXHD_BREAST_DCEMRI

[RichardObi]

Creator: RichardObi
Affiliation: UB
Stored in: https://zenodo.org/records/10210945/files/00023_PIX2PIXHD_BREAST_DCEMRI.zip?download=1

Model Metadata:

  "00023_PIX2PIXHD_BREAST_DCEMRI": {
     "execution": {
        "package_name": "00023",
        "package_link": "https://zenodo.org/record/10210945",
        "model_name": "30_net_G",
        "extension": ".pth",
        "image_size": [
           "512"
        ],
        "dependencies": [
           "numpy",
           "torch",
           "torchvision",
           "pillow"
        ],
        "generate_method": {
           "name": "generate",
           "args": {
              "base": [
                 "model_file",
                 "num_samples",
                 "output_path",
                 "save_images"
              ],
              "custom": {
                 "input_path": "input/",
                 "image_size": "512",
                 "gpu_id": "0"
              }
           }
        }
     },
     "selection": {
        "performance": {
           "SSIM": 0.726,
           "MSE": 34.88,
           "NSME": null,
           "PSNR": 32.91,
           "IS": null,
           "FID": 28.71,
           "turing_test": "",
           "downstream_task": {
              "CLF": {
                 "trained_on_fake": {
                    "accuracy": null,
                    "precision": null,
                    "recall": null,
                    "f1": null,
                    "specificity": null,
                    "AUROC": null,
                    "AUPRC": null
                 },
                 "trained_on_real_and_fake": {},
                 "trained_on_real": {}
              },
              "SEG": {
                 "trained_on_fake": {
                    "dice": 0.687,
                    "jaccard": null,
                    "accuracy": null,
                    "precision": null,
                    "recall": null,
                    "f1": null
                 },
                 "trained_on_real_and_fake": {
                    "dice": "0.797"
                 },
                 "trained_on_real": {
                    "dice": "0.790"
                 }
              }
           }
        },
        "use_cases": [
           "segmentation",
           "tumour localization",
           "classification",
           "simulation"
        ],
        "organ": [
           "breast"
        ],
        "modality": [
           "dce-mri",
           "mri",
           "t1",
           "t1-weighted",
           "fat-saturated"
        ],
        "vendors": [],
        "centres": [
           "Duke Hospital"
        ],
        "function": [],
        "condition": [],
        "dataset": [
           "DUKE"
        ],
        "augmentations": [],
        "generates": [],
        "height": 512,
        "width": 512,
        "depth": 1,
        "type": "pix2pixHD",
        "license": "BSD License",
        "dataset_type": "DCE-MRI",
        "privacy_preservation": "",
        "tags": [
           "dce-mri",
           "postcontrast",
           "synthesis",
           "breast",
           "mri",
           "treatment",
           "i2i",
           "pix2pixHD",
           "SPIE"
        ],
        "year": 2023
     },
     "description": {
        "title": "Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation",
        "provided_date": "11.2023",
        "trained_date": "2023",
        "provided_after_epoch": 30,
        "version": "1.0",
        "publication": "https://doi.org/10.48550/arXiv.2311.10879",
        "doi": [
           "https://doi.org/10.48550/arXiv.2311.10879"
        ],
        "inputs": [
           "pre-contrast t1-weighted breast mri"
        ],
        "comment": "2d breast mri slice by slice generation of postcontrast data"
     }
  }
}