  The paper introduces a novel autonomous robot ultrasound (US) system
targeting liver follow-up scans for outpatients in local communities. Given a
computed tomography (CT) image with specific target regions of interest, the
proposed system carries out the autonomous follow-up scan in three steps: (i)
initial robot contact to surface, (ii) coordinate mapping between CT image and
robot, and (iii) target US scan. Utilizing 3D US-CT registration and deep
learning-based segmentation networks, we can achieve precise imaging of 3D
hepatic veins, facilitating accurate coordinate mapping between CT and the
robot. This enables the automatic localization of follow-up targets within the
CT image, allowing the robot to navigate precisely to the target's surface.
Evaluation of the ultrasound phantom confirms the quality of the US-CT
registration and shows the robot reliably locates the targets in repeated
trials. The proposed framework holds the potential to significantly reduce time
and costs for healthcare providers, clinicians, and follow-up patients, thereby
addressing the increasing healthcare burden associated with chronic disease in
local communities.
