Enhanced Real-Time 6-DOF Extended Reality Catheter Tracking for Evaluating Potential Improvement in Efficiency, Precision, and Depth Perception for Cardiac Interventions
- URL: http://arxiv.org/abs/2608.07606v1
- Date: Thu, 06 Aug 2026 20:12:46 GMT
- Title: Enhanced Real-Time 6-DOF Extended Reality Catheter Tracking for Evaluating Potential Improvement in Efficiency, Precision, and Depth Perception for Cardiac Interventions
- Abstract summary: We developed an Extended Reality (XR)-based platform that enables real-time six-degree-of-freedom (6-DOF) catheter tracking and visualization within a patient-specific 3D heart model.<n>The system combines a custom machine-vision algorithm for 5-DOF catheter tracking with a 3D-printed electromechanical encoder that measures catheter roll, providing complete 6-DOF motion reconstruction.
- Score: 33.83106083639651
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Despite advances in 3D ultrasound, most percutaneous cardiac interventions still rely on 2D visualization, limiting depth perception and spatial understanding. To address this challenge, we developed an Extended Reality (XR)-based platform that enables real-time six-degree-of-freedom (6-DOF) catheter tracking and visualization within a patient-specific 3D heart model. The system combines a custom machine-vision algorithm for 5-DOF catheter tracking with a 3D-printed electromechanical encoder that measures catheter roll, providing complete 6-DOF motion reconstruction. In a proof-of-concept study, 20 novice medical students navigated an intracardiac echocardiography (ICE) catheter to six anatomical targets using either immersive 3D visualization or a conventional 2D cathlab-style view. Participants in the 3D condition completed the task in 54.6 seconds and traveled 1,939 mm on average, compared with 267.5 seconds and 7,854 mm in the 2D condition. Therefore, the XR-based 3D system was more than 5x faster and required ~5x less catheter travel. The 3D mode also improved targeting precision and reduced performance variability. Participants consistently rated immersive visualization higher for accuracy, speed, usability, and clinical value. Kinematic analysis showed smoother depth-axis navigation in 3D, whereas 2D users relied on repeated corrective movements. These findings demonstrate that XR-based visualization can substantially improve procedural training efficiency, precision, and motor control.
Related papers
- LeAD-M3D: Leveraging Asymmetric Distillation for Real-time Monocular 3D Detection [72.97402509843484]
LeAD-M3D is a state-of-the-art monocular 3D detector that achieves state-of-the-art accuracy and real-time inference without extra modalities.<n>Asymmetric Augmentation Denoising Distillation (A2D2) transfers geometric knowledge from a clean-image teacher to a mixup-noised student.<n>3D-aware Consistent Matching (CM3D) improves prediction-to-ground truth assignment.<n> Confidence-Gated 3D Inference (CGI3D) accelerates detection by restricting expensive 3D regression to top-confidence regions.
arXiv Detail & Related papers (2025-12-05T12:08:18Z) - 4D Virtual Imaging Platform for Dynamic Joint Assessment via Uni-Plane X-ray and 2D-3D Registration [17.77433522588242]
We propose an integrated 4D joint analysis platform that combines a dual robotic arm cone-beam (CBCT) system with a programmable, gantry-free trajectory optimized for upright scanning.<n>In simulation studies, the method achieved sub-voxel accuracy (0.235 mm) with a 99.18 percent success rate, outperforming conventional and state-of-the-art registration approaches.<n>This 4D CBCT platform enables fast, accurate, and low-dose dynamic joint imaging, offering new opportunities for biomechanical research, precision diagnostics, and personalized orthopedic care.
arXiv Detail & Related papers (2025-08-22T06:58:23Z) - 3D Heart Reconstruction from Sparse Pose-agnostic 2D Echocardiographic Slices [6.275809518974307]
We propose an innovative framework for reconstructing personalized 3D heart anatomy from 2D echo slices.<n>When six planes are used, the reconstructed 3D heart can lead to a significant improvement for LV volume estimation.<n>This study provides a new way for personalized 3D structure and function analysis from cardiac ultrasound.
arXiv Detail & Related papers (2025-07-03T08:13:07Z) - MedTet: An Online Motion Model for 4D Heart Reconstruction [59.74234226055964]
We present a novel approach to reconstruction of 3D cardiac motion from sparse intraoperative data.<n>Existing methods can accurately reconstruct 3D organ geometries from full 3D volumetric imaging.<n>We propose a versatile framework for reconstructing 3D motion from such partial data.
arXiv Detail & Related papers (2024-12-03T17:18:33Z) - Advanced XR-Based 6-DOF Catheter Tracking System for Immersive Cardiac Intervention Training [37.69303106863453]
This paper presents a novel system for real-time 3D tracking and visualization of intracardiac echocardiography (ICE) catheters.
A custom 3D-printed setup captures biplane video of the catheter, while a specialized computer vision algorithm reconstructs its 3D trajectory.
The system's data is integrated into an interactive Unity-based environment, rendered through the Meta Quest 3 XR headset.
arXiv Detail & Related papers (2024-11-04T21:05:40Z) - UniPAD: A Universal Pre-training Paradigm for Autonomous Driving [74.34701012543968]
We present UniPAD, a novel self-supervised learning paradigm applying 3D differentiable rendering.
UniPAD implicitly encodes 3D space, facilitating the reconstruction of continuous 3D shape structures.
Our method significantly improves lidar-, camera-, and lidar-camera-based baseline by 9.1, 7.7, and 6.9 NDS, respectively.
arXiv Detail & Related papers (2023-10-12T14:39:58Z) - MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View
Cardiac MRI [11.685829837689404]
We propose a novel multi-view motion estimation network (MulViMotion) to learn a consistent 3D motion field of the heart.
We extensively evaluate the proposed method on 2D cine CMR images from 580 subjects of the UK Biobank study for 3D motion tracking of the left ventricular myocardium.
arXiv Detail & Related papers (2022-07-29T18:29:52Z) - Revisiting 3D Context Modeling with Supervised Pre-training for
Universal Lesion Detection in CT Slices [48.85784310158493]
We propose a Modified Pseudo-3D Feature Pyramid Network (MP3D FPN) to efficiently extract 3D context enhanced 2D features for universal lesion detection in CT slices.
With the novel pre-training method, the proposed MP3D FPN achieves state-of-the-art detection performance on the DeepLesion dataset.
The proposed 3D pre-trained weights can potentially be used to boost the performance of other 3D medical image analysis tasks.
arXiv Detail & Related papers (2020-12-16T07:11:16Z) - 3D Probabilistic Segmentation and Volumetry from 2D projection images [10.32519161805588]
X-Ray imaging is quick, cheap and useful for front-line care assessment and intra-operative real-time imaging.
It suffers from projective information loss and lacks vital information on which many essential diagnostic biomarkers are based.
In this paper we explore probabilistic methods to reconstruct 3D volumetric images from 2D imaging modalities.
arXiv Detail & Related papers (2020-06-23T08:00:51Z) - Volumetric Attention for 3D Medical Image Segmentation and Detection [53.041572035020344]
A volumetric attention(VA) module for 3D medical image segmentation and detection is proposed.
VA attention is inspired by recent advances in video processing, enables 2.5D networks to leverage context information along the z direction.
Its integration in the Mask R-CNN is shown to enable state-of-the-art performance on the Liver Tumor (LiTS) Challenge.
arXiv Detail & Related papers (2020-04-04T18:55:06Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.