Autonomous Robotic Ultrasound System for Liver Follow-up Diagnosis: Pilot Phantom Study

Tianpeng Zhang, Sekeun Kim, Jerome Charton, Haitong Ma, Kyungsang Kim +2 more
5/9/2024
cs.ROcs.CVeess.SY

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Abstract

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.

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Cite this paper

@article{zhang2024autonomous,
  title  = {Autonomous Robotic Ultrasound System for Liver Follow-up Diagnosis: Pilot Phantom Study},
  author = {Tianpeng Zhang and Sekeun Kim and Jerome Charton and Haitong Ma and Kyungsang Kim and Na Li and Quanzheng Li},
  year   = {2024},
  eprint = {2405.05787},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.05787v1}
}

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