Towards Automated Initial Probe Placement in Transthoracic Teleultrasound Using Human Mesh and Skeleton Recovery
This addresses the problem of automating probe placement for novices or robots in teleultrasound, though it appears incremental as it builds on existing human mesh and skeleton recovery techniques.
The paper tackles the challenge of initial probe placement in transthoracic teleultrasound by developing a framework using RGB images to infer patient-specific body and skeleton models for guidance, with pilot experiments showing consistent placement within acceptable anatomical variability.
Cardiac and lung ultrasound are technically demanding because operators must identify patient-specific intercostal acoustic windows and then navigate between standard views by adjusting probe position, rotation, and force across different imaging planes. These challenges are amplified in teleultrasound when a novice or robot faces the difficult task of first placing the probe on the patient without in-person expert assistance. We present a framework for automating Patient registration and anatomy-informed Initial Probe placement Guidance (PIPG) using only RGB images from a calibrated camera. The novice first captures the patient using the camera on a mixed reality (MR) head-mounted display (HMD). An edge server then infers a patient-specific body-surface and skeleton model, with spatial smoothing across multiple views. Using bony landmarks from the predicted skeleton, we estimate the intercostal region and project the guidance back onto the reconstructed body surface. To validate the framework, we overlaid the reconstructed body mesh and the virtual probe pose guidance across multiple transthoracic echocardiography scan planes in situ and measured the quantitative placement error. Pilot experiments with healthy volunteers suggest that the proposed probe placement prediction and MR guidance yield consistent initial placement within anatomical variability acceptable for teleultrasound setup