Towards Autonomous Atlas-based Ultrasound Acquisitions in Presence of Articulated Motion

TL;DR

This paper presents a vision-based autonomous robotic ultrasound system that uses an atlas MRI template and neural networks to generate and execute optimal limb scanning trajectories, successfully capturing vascular structures across different subjects.

Contribution

It introduces a novel atlas-based trajectory planning method combined with a neural network for vessel segmentation, enabling autonomous US limb scanning despite articulated joint movements.

Findings

Successful acquisition of vascular structures on six volunteers with various joint angles.

Accurate artery radius estimation ($1.2 ext{mm}$) comparable to MRI ground truth.

Robust autonomous US scanning demonstrated across diverse anatomical configurations.

Abstract

Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e.g. difficulty in guaranteeing intra- and inter-operator repeatability. However, due to anatomical and physiological variations between patients and relative movement of anatomical substructures, it is challenging to robustly generate optimal trajectories to examine the anatomies of interest, in particular, when they comprise articulated joints. To address this challenge, this paper proposes a vision-based approach allowing autonomous robotic US limb scanning. To this end, an atlas MRI template of a human arm with annotated vascular structures is used to generate trajectories and register and project them onto patients' skin surfaces for robotic US acquisition. To effectively segment and accurately reconstruct the targeted 3D vessel, we make use of spatial continuity in consecutive US frames by incorporating channel attention modules into a U-Net-type neural network. The automatic trajectory generation method is evaluated on six volunteers with various articulated joint angles. In all cases, the system can successfully acquire the planned vascular structure on volunteers' limbs. For one volunteer the MRI scan was also available, which allows the evaluation of the average radius of the scanned artery from US images, resulting in a radius estimation ($1.2\pm0.05~mm$) comparable to the MRI ground truth ($1.2\pm0.04~mm$).