MLRecon: Robust Markerless Freehand 3D Ultrasound Reconstruction via Coarse-to-Fine Pose Estimation

• URL: http://arxiv.org/abs/2603.00990v1
• Date: Sun, 01 Mar 2026 08:39:21 GMT
• Title: MLRecon: Robust Markerless Freehand 3D Ultrasound Reconstruction via Coarse-to-Fine Pose Estimation
• Authors: Yi Zhang, Puxun Tu, Kun Wang, Yulin Yan, Tao Ying, Xiaojun Chen,
• Abstract summary: We present MLRecon, a robust markerless 3D US reconstruction framework delivering drift-resilient 6D probe pose tracking.<n>Our pipeline enables continuous markerless tracking of the probe, augmented by a vision-guided divergence detector.<n>Experiments demonstrate that MLRecon significantly outperforms competing sensorless and sensor-aided methods.
• Score: 8.489758968497188
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Freehand 3D ultrasound (US) reconstruction promises volumetric imaging with the flexibility of standard 2D probes, yet existing tracking paradigms face a restrictive trilemma: marker-based systems demand prohibitive costs, inside-out methods require intrusive sensor attachment, and sensorless approaches suffer from severe cumulative drift. To overcome these limitations, we present MLRecon, a robust markerless 3D US reconstruction framework delivering drift-resilient 6D probe pose tracking using a single commodity RGB-D camera. Leveraging the generalization power of vision foundation models, our pipeline enables continuous markerless tracking of the probe, augmented by a vision-guided divergence detector that autonomously monitors tracking integrity and triggers failure recovery to ensure uninterrupted scanning. Crucially, we further propose a dual-stage pose refinement network that explicitly disentangles high-frequency jitter from low-frequency bias, effectively denoising the trajectory while maintaining the kinematic fidelity of operator maneuvers. Experiments demonstrate that MLRecon significantly outperforms competing sensorless and sensor-aided methods, achieving average position errors as low as 0.88 mm on complex trajectories and yielding high-quality 3D reconstructions with sub-millimeter mean surface accuracy. This establishes a new benchmark for low-cost, accessible volumetric US imaging in resource-limited clinical settings.

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