# multimodars: A Rust-powered toolkit for multi-modality cardiac image fusion and registration

arXiv: https://arxiv.org/abs/2510.06241 · HTML: https://mlsanity.com/paper/2510.06241/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 3 Oct 2025.

## Abstract (arXiv)

Combining complementary imaging modalities is critical to build reliable 3D coronary models: intravascular imaging gives sub-millimetre resolution but limited whole-vessel context, while CCTA supplies 3D geometry but suffers from limited spatial resolution and artefacts (e.g., blooming). Prior work demonstrated intravascular/CCTA fusion, yet no open, flexible toolkit is tailored for multi-state analysis (rest/stress, pre-/post-stenting) while offering deterministic behaviour, high performance, and easy pipeline integration. multimodars addresses this gap with deterministic alignment algorithms, a compact NumPy-centred data model, and an optimised Rust backend suitable for scalable, reproducible experiments. The package accepts CSV/NumPy inputs including data formats produced by the AIVUS-CAA software