Representing and Mapping 3D Imaging and Spatial-omics Data Simultaneously Across Scales with Image-Varifold

by Benjamin Charlier (Inrae)

Friday Jun 13, 2025, 11:00 AM → 12:00 PM Europe/Paris

Recent advances in imaging and molecular profiling technologies have enabled the acquisition of data at subcellular resolution. However, integrating such data across modalities, spatial scales, and acquisition protocols remains a major challenge due to differences in resolution, feature types, and physical coverage.
In this talk, I will present a suite of technologies we have developed for cross-modality 3D mapping, enabling non-rigid alignment of transcriptomic data at micron scales (genes and cells) to anatomical structures at tissue and organ scales. Our approach addresses three key challenges:

1. **Comparing diverse modalities** using the mathematical framework of image-varifold norms
2. **Managing massive data volumes** through a multiscale strategy for computing non-rigid deformations efficiently
3. **Handling incomplete data** via partial matching methods that map full-brain references to sparsely sampled sub-volumes

We introduce **xIV-LDDMM**, a cross-modality image-varifold Large Deformation Diffeomorphic Metric Mapping toolkit. This framework enables efficient representation and registration of peta-scale datasets, bridging spatial scales from nanometers to millimeters.

These methods are detailed in:

- Stouffer KM, Chen X, Zeng H, Charlier B., *et al.* _xIV-LDDMM Toolkit: A Suite of Image-Varifold Based Technologies for Representing and Mapping 3D Imaging and Spatial-omics Data Simultaneously Across Scales_. Submitted. 2025. [PubMed](https://pubmed.ncbi.nlm.nih.gov/39574713)
- Stouffer KM, Trouvé A, Younès L, Kunst M., *et al.* _Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections_. *Nat Commun.* 2024 Apr 25;15(1):3530. [PubMed](https://pubmed.ncbi.nlm.nih.gov/38664422)