📝 SummarXiv

Abstract

Echocardiography is a key imaging modality for cardiac assessment but remains highly operator-dependent, and access to trained sonographers is limited in underserved settings. Teleoperated robotic echocardiography has been proposed as a solution; however, clinical studies report longer examination times than manual procedures, increasing diagnostic delays and operator workload. Automating non-expert tasks, such as automatically moving the probe to an ideal starting pose, offers a pathway to reduce this burden. Prior vision- and depth-based approaches to estimate an initial probe pose are sensitive to lighting, texture, and anatomical variability. We propose a robot-mounted 2D LiDAR-based approach that reconstructs the chest surface in 3D and estimates the initial probe pose automatically. To the best of our knowledge, this is the first demonstration of robot-mounted 2D LiDAR used for 3D reconstruction of a human body surface. Through plane-based extrinsic calibration, the transformation between the LiDAR and robot base frames was estimated with an overall root mean square (RMS) residual of 1.8 mm and rotational uncertainty below 0.2{\deg}. The chest front surface, reconstructed from two linear LiDAR sweeps, was aligned with non-rigid templates to identify an initial probe pose. A mannequin-based study assessing reconstruction accuracy showed mean surface errors of 2.78 +/- 0.21 mm. Human trials (N=5) evaluating the proposed approach found probe initial points typically 20-30 mm from the clinically defined initial point, while the variation across repeated trials on the same subject was less than 4 mm.