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license: cc-by-4.0
---

# SMMILe: WSI Embedding Superpixel Data, and Checkpoints

This repository contains embedding superpixel segmentation and checkpoint data for six publicly available whole-slide image (WSI) datasets. The embeddings were generated using two different encoders: ResNet-50 and Conch. Each dataset is available as a ZIP file containing both the embeddings and the corresponding superpixel segmentation results.

## Datasets and Files

Checkpoints of SMMILe for different datasets and encoders are all saved in `ckpt_submit.zip`.

The rest of the ZIP files contain the embeddings and superpixel segmentations for one dataset, which are processed using either ResNet-50 or Conch. The files are stored using Git LFS due to their large size.

### File Overview:

| Dataset          | Encoder       | File Name                | Size     |
|------------------|---------------|--------------------------|----------|
| Breast           | Conch         | `camel_conch.zip`        | 5.76 GB  |
| Breast           | ResNet-50     | `camel_res50.zip`        | 17.5 GB  |
| Gastric          | Conch         | `gastric_conch.zip`      | 489 MB   |
| Gastric          | ResNet-50     | `gastric_res50.zip`      | 1.13 GB  |
| Lung             | Conch         | `lung_conch.zip`         | 1.4 GB   |
| Lung             | ResNet-50     | `lung_res50.zip`         | 3.12 GB  |
| Ovarian          | Conch         | `ovarian_conch.zip`      | 2.5 GB   |
| Ovarian          | ResNet-50     | `ovarian_res50.zip`      | 6.42 GB  |
| Prostate         | Conch         | `prostate_conch.zip`     | 35.6 MB  |
| Prostate         | ResNet-50     | `prostate_res50.zip`     | 69.1 MB  |
| Renal-3          | Conch         | `renal3_conch.zip`       | 1.47 GB  |
| Renal-3          | ResNet-50     | `renal3_res50.zip`       | 3.2  GB  |

## Structure of Each ZIP File:

Each ZIP file contains two folders:
- **Model Embeddings**: Embeddings for patches extracted from WSIs, stored as `.npy` files.
- **Superpixel Segmentations**: Corresponding superpixel segmentation results for each WSI, stored as `.npy` files.

### Example File Structure:

```plaintext
camel_res50.zip
  ├── resnet50/            # ResNet-50 embeddings (1024-dimensional)
  └── sp_xxx/              # Superpixel segmentations

gastric_conch.zip
  ├── conch/               # Conch embeddings (512-dimensional)
  └── sp_xxx/              # Superpixel segmentations
```

## Embeddings (.npy Files):

**Keys in the Embedding Files:**
- `'feature'`: Embedding vectors of image patches.
- `'inst_label'`: Annotated label of each patch. A value of `-1` indicates a non-annotated patch.
- `'index'`: Coordinates and size of the patch in the format `x_y_size`, where `x` and `y` represent the top-left coordinates.

## Superpixel Segmentations (.npy Files):

**Keys in the Superpixel Files:**
- `'m_slic'`: Superpixel index for each patch.
- `'m_adj'`: Adjacency matrix representing the relationships between superpixels.