Summary: High-performance toolkit for aligning and fusing cardiac imaging from CCTA, IVUS, OCT, and MRI
multimodars is a high-performance, Rust-accelerated toolkit designed to address the complex challenge of aligning and fusing diverse cardiac imaging modalities into unified, high-resolution 3D models. The package seamlessly integrates data from coronary computed tomography angiography (CCTA), intravascular ultrasound (IVUS), optical coherence tomography (OCT), and cardiac MRI, leveraging Rust’s computational efficiency for registration steps that would be prohibitively slow in pure Python implementations. The toolkit was initially developed to study dynamic vessel deformation in coronary artery anomalies, where quantifying lumen changes under stress and rest conditions is clinically critical.
The software features sophisticated IVUS/OCT contour registration using Hausdorff distance metrics on vessel contours and catheter centroids, supporting multiple alignment modes including full four-phase registration (rest-diastole, rest-systole, stress-diastole, stress-systole), double-pair, single-pair, and single-phase alignments. Beyond coronary anomalies, multimodars serves as a general-purpose toolkit applicable to longitudinal studies such as pre- and post-stenting comparisons in percutaneous coronary interventions. Available through PyPI for easy installation, the package includes comprehensive documentation, example Jupyter notebooks, and utilities for smoothing contours, computing geometric metrics, and exporting aligned geometries for visualization and further analysis.