Echo-POSED: Geometric Self-Distillation for Echocardiography Guidance
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Abstract (arXiv)
We introduce Echo-POSED, a self-supervised framework for real-time transthoracic echocardiography (TTE) guidance that recommends probe adjustments directly from 2D ultrasound images, without the need for expert-labelled views or tracked probe trajectories. Instead, it trains on 2D views sliced from routinely acquired 3D echocardiography volumes, enforcing equivariance to probe motions while remaining invariant to cardiac phase, yielding a pose representation on SO(3)×SO(3). Across a held-out split and public external 3D--TTE datasets (including vendor shift), Echo-POSED maintains geometric consistency under virtual perturbations and enables intra- and inter-patient guidance simulations, achieving a combined mean angular error of 8.2 degrees between the guided and target views in intra-patient simulations with cardiac motion.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 41 references that are in the map. First posted on arXiv 30 May 2026.
Builds on
10 of 41 references.
References · 10
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,214
- 2020An Analysis of SVD for Deep Rotation Estimationcited by 86
- 2020Automatic Probe Movement Guidance for Freehand Obstetric Ultrasoundcited by 28
- 2024Machine Learning in Robotic Ultrasound Imaging: Challenges and Perspectivescited by 17
- 2018Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Networkcited by 15
- 2025EchoWorld: Learning Motion-Aware World Models for Echocardiography Probe Guidancecited by 15
- 2024Structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-traincited by 7
- 2024AI-driven View Guidance System in Intra-cardiac Echocardiography Imagingcited by 3
- 2024Pose-GuideNet: Automatic Scanning Guidance for Fetal Head Ultrasound from Pose Estimationcited by 2
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Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
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- 2024Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation
- 2024Cardiac Copilot: Automatic Probe Guidance for Echocardiography with World Model
- 2026EchoDiST: Self-distillation-based joint learning for diffusion-conditioned echocardiographic myocardial motion estimation
- 2024HeartBeat: Towards Controllable Echocardiography Video Synthesis with Multimodal Conditions-Guided Diffusion Models
- 2026Echo4DIR: 4D Implicit Heart Reconstruction from 2D Echocardiography Videos
- 2026SonoWorld: Towards Interactive Pose-Controllable Ultrasound World Models
- 2026EchoTracker2: Enhancing Myocardial Point Tracking by Modeling Local Motion
- 2024Graph Convolutional Neural Networks for Automated Echocardiography View Recognition: A Holistic Approach