MCD Stitcher

MCD Stitcher turns raw Imaging Mass Cytometry (IMC) .mcd files from Standard BioTools instruments into ordinary image files you can open in QuPath, Napari, or Fiji.

It can:

• Convert each region (ROI) in an .mcd file into its own OME-TIFF.
• Stitch all regions back together into a single whole-slide OME-TIFF.
• Tidy up OME-TIFFs afterwards — keep only the channels you want, shrink them for fast viewing, or re-compress them.

📄 Using MCD Stitcher in your research? Please cite the preprint.

🚀 Quick Start

MCD Stitcher needs Python 3.9 or newer:

pip install mcd_stitcher

Then point mcd_process at a single .mcd file (or a whole folder of them):

# Convert every region to its own OME-TIFF AND stitch them into one whole-slide OME-TIFF
mcd_process "path/to/file.mcd" --convert --stitch

Results land in a MCD_Processed/<file name>/ folder next to your input:

MCD_Processed/<file name>/
├── <region>.ome.tiff                       # one per region          --convert
├── <file name>_stitched.ome.tiff           # whole-slide mosaic      --stitch
├── <file name>_slide_0_pano_0.png          # panorama overview       -p
├── <file name>_slide_0_pano_0_overlay.png  # panorama + ROI outlines -p
└── <file name>_slide_0_pano_0_roi_map.txt  # region → panorama px     --roi_map

Post-processing adds <name>_filtered.ome.tiff (-f) and <name>_pyramid.ome.tiff (--pyramid) alongside the originals.

⚡ Commands

mcd_process is the one command you need — a .mcd file (or a folder of them) in, your OME-TIFFs out. Everything below is mcd_process; the single-purpose tools are optional.

I want to…

Every option

mcd_process <input_path> [<output_path>] [OPTIONS]

🔧 Single-purpose commands & Python API

Only need one step? mcd_stitch and mcd_convert do exactly that. tiff_subset works on existing OME-TIFFs (channels / pyramids / --list-channels).

mcd_stitch  <input_path> [<output_path>] [-d TYPE] [-c MODE] [-r "LIST"]
mcd_convert <input_path> [<output_path>] [-d TYPE] [-c MODE]
tiff_subset <input_path> [<output_path>] [-l | -f "LIST" | -p]

Single .mcd in for the first two (folders are batched by mcd_process). tiff_subset takes a .tiff or a directory; directory mode scans *.tiff recursively and logs per-file failures to ome_subset_errors.log.

from pathlib import Path
from mcd_stitcher import mcd_stitch, mcd_convert, mcd_process

mcd_process(input_path=Path("file.mcd"), convert=True, stitch=True, panorama="all")

from mcd_stitcher import __version__ returns the installed package version.

📄 Citation

If you use MCD Stitcher in your research, please cite:

Chaurasia, P. (2026). MCD Stitcher: An open-source tool for whole-slide stitching and conversion of Imaging Mass Cytometry data. bioRxiv. https://doi.org/10.64898/2026.06.26.732348

@article{chaurasia2026mcdstitcher,
  title   = {MCD Stitcher: An open-source tool for whole-slide stitching and conversion of Imaging Mass Cytometry data},
  author  = {Chaurasia, Pawan},
  journal = {bioRxiv},
  year    = {2026},
  doi     = {10.64898/2026.06.26.732348},
  url     = {https://doi.org/10.64898/2026.06.26.732348}
}

📜 License

Distributed under the MIT License. See LICENSE.

💬 Issues & Changelog

If you run into issues, have a feature suggestion, or want to share feedback, please open a ticket on the issue tracker. Release notes for every version are in the changelog.