MLRecon: Robust Markerless Freehand 3D Ultrasound Reconstruction via Coarse-to-Fine Pose Estimation
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Abstract (arXiv)
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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References · 13
- 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
- 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,214
- 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 429
- 2018Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registrationcited by 40
- 2022Deep Motion Network for Freehand 3D Ultrasound Reconstructioncited by 14
- 2025SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentationcited by 8
- 2023Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Trackercited by 7
- 2024Fine-grained Context and Multi-modal Alignment for Freehand 3D Ultrasound Reconstructioncited by 5
- 2025MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstructioncited by 3
- 20243D Freehand Ultrasound using Visual Inertial and Deep Inertial Odometry for Measuring Patellar Trackingcited by 2
- 2025Enhancing Free-hand 3D Photoacoustic and Ultrasound Reconstruction using Deep Learningcited by 2
- 2025DualTrack: Sensorless 3D Ultrasound needs Local and Global Contextcited by 2
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