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roobee79
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HNE2Cell

Image Segmentation
PyTorch
hne2cell
cell-classification
cell-detection
digital-pathology
whole-slide-image
H&E
computational-pathology
Model card Files
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HNE2Cell
File size: 1,300 Bytes
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{
  "model_type": "hne2cell",
  "architecture": "CellViT",
  "task": "image-segmentation",
  "description": "H&E whole-slide image cell detection and classification (16 cell types).",
  "weights_file": "HNE2cell_pub_patch73_jit.pt",
  "weights_format": "torchscript",
  "framework": "pytorch",
  "input_size": [256, 256],
  "input_channels": 3,
  "recommended_magnification": 40,
  "supported_magnifications": [40, 20],
  "patch_overlap": 64,
  "num_classes": 16,
  "id2label": {
    "0": "Background",
    "1": "Malignant",
    "2": "CD4 T",
    "3": "CD8 T",
    "4": "B",
    "5": "Plasma",
    "6": "Macrophage",
    "7": "Myeloid",
    "8": "DC",
    "9": "Fibroblast",
    "10": "Endothelial",
    "11": "Pericyte",
    "12": "Epithelial",
    "13": "Immune_Other",
    "14": "Stromal_Other",
    "15": "Dead"
  },
  "label2id": {
    "Background": 0,
    "Malignant": 1,
    "CD4 T": 2,
    "CD8 T": 3,
    "B": 4,
    "Plasma": 5,
    "Macrophage": 6,
    "Myeloid": 7,
    "DC": 8,
    "Fibroblast": 9,
    "Endothelial": 10,
    "Pericyte": 11,
    "Epithelial": 12,
    "Immune_Other": 13,
    "Stromal_Other": 14,
    "Dead": 15
  },
  "normalization": "reinhard_lab",
  "normalization_reference": "standard-ilc.tif",
  "license": "cc-by-nc-4.0",
  "_name_or_path": "roobee79/HNE2Cell"
}