Datasets:
File size: 2,893 Bytes
e043529 e38da7e e043529 68156be e38da7e e043529 ac41c0b e043529 68156be ac41c0b e043529 68156be e043529 68156be e043529 68156be e043529 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | ---
license: other
license_name: ohsu-non-commercial
license_link: https://github.com/ChangLab/miniMTI/blob/publication/LICENSE
tags:
- biology
- multiplex-imaging
- computational-pathology
- cycif
- colorectal-cancer
size_categories:
- 1K<n<10K
---
# miniMTI-CRC Example Data
Example single-cell imaging data for testing [miniMTI](https://huggingface.co/changlab/miniMTI-CRC), a molecularly anchored virtual staining framework for multiplex tissue imaging panel reduction.
**Paper:** [bioRxiv 2026.01.21.700911](https://www.biorxiv.org/content/10.64898/2026.01.21.700911v1)
**Code:** [GitHub](https://github.com/ChangLab/miniMTI)
**Model:** [changlab/miniMTI-CRC](https://huggingface.co/changlab/miniMTI-CRC)
## Dataset Description
10,000 single-cell image patches randomly sampled (seed=42) from CRC-Orion sample CRC04 (colorectal cancer tissue WSI, RareCyte Orion platform).
### File
- `example_CRC04_10k.h5` — HDF5 file (~178 MB)
### HDF5 Structure
| Dataset | Shape | Type | Description |
|------------|--------------------|--------|-------------|
| `images` | (10000, 32, 32, 20)| uint8 | 17 IF channels + 3 H&E (RGB) channels |
| `masks` | (10000, 32, 32) | bool | Binary cell segmentation masks |
| `metadata` | (10000,) | string | Cell IDs and coordinates: `<sample>-CellID-<id>-x=<x>-y=<y>` |
### Channel Ordering (20 raw channels)
| Index | Channel |
|-------|-------------|
| 0 | DAPI |
| 1 | CD31 |
| 2 | CD45 |
| 3 | CD68 |
| 4 | CD4 |
| 5 | FOXP3 |
| 6 | CD8a |
| 7 | CD45RO |
| 8 | CD20 |
| 9 | PD-L1 |
| 10 | CD3e |
| 11 | CD163 |
| 12 | E-cadherin |
| 13 | PD-1 |
| 14 | Ki67 |
| 15 | PanCK |
| 16 | aSMA |
| 17 | H&E (R) |
| 18 | H&E (G) |
| 19 | H&E (B) |
Channels 0–16 are immunofluorescence markers. Channels 17–19 are co-registered H&E RGB. The miniMTI model treats each IF channel as a separate marker and the three H&E channels as a single marker (18 markers total).
## Usage
```python
from huggingface_hub import hf_hub_download
# Download example data
path = hf_hub_download(
repo_id="changlab/miniMTI-CRC-example",
filename="example_CRC04_10k.h5",
repo_type="dataset",
)
```
```bash
# Run inference with miniMTI
python scripts/inference_example.py \
--val-file $path \
--input-channels 17,6,11,13
```
## Citation
```bibtex
@article{sims2026minimti,
title={miniMTI: minimal multiplex tissue imaging enhances biomarker expression prediction from histology},
author={Sims, Z. and Govindarajan, S. and Ait-Ahmad, K. and Ak, C. and Kuykendall, M. and Mills, G. B. and Eksi, E. and Chang, Y. H.},
journal={bioRxiv},
year={2026},
doi={10.64898/2026.01.21.700911}
}
```
|