Surgical pathology
Medical specialty dedicated to analyzing tissues and cells
In 2025, 95% of cancer diagnosis rely on surgical pathology.
As demand grows, pathologists are under increasing pressure to deliver faster results while maintaining exceptional accuracy.
Despite recent advances in digital pathology and AI tools, two bottlenecks remain:Â staining samples and interpreting them efficiently.
Introducing MirStain
Infrared imaging for enhanced digital staining
Technical details
MIRStain uses infrared light to caracterize biological tissues. Our deep learning model then use these data to digitaly stain samples. This allows to skip chemical staining processes, cuting down on cost and time-to-result. This process can also be used for diagnosis and metabolomics.
100% diagnostic time reduction
30% laboratory costs reduction
30% less water and chemicals
95% analysis accuracy
Preliminary results
Further results
Clinical Feasibility of Label-Free Digital Staining Using Mid-Infrared Microscopy at Subcellular Resolution
L. Duraffourg, H. Borges, M. Fernandes, M. Beurrier-Bousquet, J. Baraillon, B. Taurel, J. Le Galudec, K. Vianey, C. Maisin, L. Samaison, F. Staroz, M. Dupoy (2026, preprint)
We present a rapid, large-field bimodal imaging platform that integrates conventional brightfield microscopy with a lensless IR imaging scanner, enabling whole-slide IR image stack acquisition in minutes. Using a dedicated deep learning model, we implement an optical HE staining strategy based on subcellular morpho-spectral fingerprinting.
White paper
In a few pages, get a full overview of the context of our work and the ambitions of ADMIR regarding Anatomic Pathology.