Optimization-Based Calibration for Intravascular Ultrasound Volume Reconstruction

2025-08-28

AI Summary

In liver surgery, accurate registration between preoperative CT and intraoperative intravascular ultrasound (IVUS) images remains challenging due to limited IVUS field-of-view and complex hepatic anatomy. To address this, we propose an optimization-based calibration framework leveraging a 3D-printed vascular phantom. Our method integrates real-time IVUS tracking, nonlinear optimization, and comprehensive in vitro/in vivo validation to achieve high-fidelity 3D IVUS reconstruction and precise spatial alignment with CT coordinates. A key innovation is the development of a reproducible physical simulation platform that substantially reduces the spatial discrepancy between preoperative planning and intraoperative reality. In live porcine liver experiments, the proposed framework achieves a calibration error of 0.88–1.80 mm and a CT–IVUS 3D registration error of 3.40–5.71 mm—demonstrating improved accuracy and robustness over existing approaches. This work establishes a reliable navigation foundation for real-time ultrasound-guided liver surgery.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Intraoperative ultrasound images are inherently challenging to interpret in liver surgery due to the limited field of view and complex anatomical structures. Bridging the gap between preoperative and intraoperative data is crucial for effective surgical guidance. 3D IntraVascular UltraSound (IVUS) offers a potential solution by enabling the reconstruction of the entire organ, which facilitates registration between preoperative computed tomography (CT) scans and intraoperative IVUS images. In this work, we propose an optimization-based calibration method using a 3D-printed phantom for accurate 3D Intravascular Ultrasound volume reconstruction. Our approach ensures precise alignment of tracked IVUS data with preoperative CT images, improving intraoperative navigation. We validated our method using in vivo swine liver images, achieving a calibration error from 0.88 to 1.80 mm and a registration error from 3.40 to 5.71 mm between the 3D IVUS data and the corresponding CT scan. Our method provides a reliable and accurate means of calibration and volume reconstruction. It can be used to register intraoperative ultrasound images with preoperative CT images in the context of liver surgery, and enhance intraoperative guidance.

Problem

• Bridging preoperative CT and intraoperative ultrasound data gap
• Enabling accurate 3D IVUS volume reconstruction for liver surgery
• Improving calibration and registration between CT and ultrasound images

Innovation

• Optimization-based calibration with 3D-printed phantom
• Precise alignment of IVUS data with CT images
• Validated using in vivo swine liver images