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