The TransNav consortium project, titled “3‑D Multimodal Navigation System for Transvascular Interventions,” was carried out at the University of Ulm from 1 October 2019 to 31 March 2023 under the German Federal Ministry of Education and Research grant 13GW0372E. The project aimed to simplify the planning and execution of catheter‑based transvascular procedures, which in current practice are complex, time‑consuming, and expose patients to high radiation doses. The consortium’s partners, including the University of Ulm and several clinical and research institutions, collaborated to develop a demonstrator that integrates advanced registration, navigation, and visualization techniques to reduce contrast‑agent usage, radiation exposure, and intervention duration while providing a robust documentation framework for postoperative analysis.

Technically, the project focused on multimodal 3‑D visualization of cardiac imaging data. The team extended the open‑source Inviwo visualization framework to support live X‑ray image updates and the extraction of imaging parameters using the OpenCV library. Volumetric rendering of CT and MRI volumes was implemented, along with slice‑by‑slice displays aligned with the main axes. Segmented anatomical structures—organs, bones, and vessels—were represented as meshes and fused with the live fluoroscopic view. A simple DICOM exporter was added to store extracted parameters and image data in structured DICOM files, enabling seamless integration with hospital information systems.

A key innovation was the development of a multi‑view system that synchronizes several perspectives, allowing clinicians to view the patient’s anatomy, the catheter trajectory, and the fluoroscopic image simultaneously. Focus‑and‑context techniques were applied to hide irrelevant data and highlight the entities relevant to the current procedural step, thereby reducing visual clutter. The Mathematical Expression Toolkit Library was integrated to evaluate camera parameters in real time, ensuring that the virtual view accurately matches the physician’s perspective on the C‑arm. Vessel‑tree visualization methods were also introduced, enabling the identification of critical branching points and facilitating navigation without continuous reliance on X‑ray imaging.

The demonstrator was built as a central platform where all partner algorithms could be integrated. It supports interactive navigation, real‑time updates of imaging data, and a standardized documentation workflow that captures procedural steps without imposing additional burdens on the operator. Although specific quantitative performance metrics such as reduction percentages in radiation dose or contrast usage were not reported in the excerpt, the system’s design explicitly targets these outcomes and provides a foundation for future clinical evaluation.

Collaboration-wise, the University of Ulm served as the project lead, coordinating the integration of software components and ensuring compatibility with the hospital’s existing systems. Other consortium members contributed specialized algorithms for image registration, segmentation, and visualization, and participated in iterative testing and refinement of the demonstrator. The project’s timeline spanned 3 ½ years, during which the team progressed from establishing coordinate systems and live image acquisition to deploying a fully functional multimodal navigation tool. The funding from the German Federal Ministry of Education and Research enabled the acquisition of necessary hardware, software licenses, and personnel resources, culminating in a demonstrator that promises to streamline catheter‑based transvascular interventions and improve patient safety.