| --- |
| 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} |
| } |
| ``` |
|
|
