Robust Robotic Breast Ultrasound Scanning and Real-Time Lesion Localization
Zhiyan Cao, Yiwei Wang, Huan Zhao, Han Ding, Shaohua Zhang
Abstract
The inherent flexibility and real-time deformation of breast tissue pose significant challenges for achieving full coverage and accurate lesion localization in autonomous breast ultrasound scanning. This paper introduces a robust finite state machine-based framework that mimics the decision-making process of an experienced physician, dynamically transitioning between the global breast scan and the fine lesion scan. An autonomous radial and anti-radial global scan pattern ensures comprehensive breast coverage. To avoid lesion misidentification caused by soft tissue movement, a real-time lesion fine scan method is proposed for lesion detection and localization. Experimental results demonstrate that the system in full coverage tests achieves 7 identified lesions out of 7 existing lesions and maintains a robust localization accuracy of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{3. 2 3 ~ m m}$</tex> across phantoms with varying stiffnesses.
BibTeX
@inproceedings{icra2025_robustroboticbre,
title = {Robust Robotic Breast Ultrasound Scanning and Real-Time Lesion Localization},
author = {Zhiyan Cao and Yiwei Wang and Huan Zhao and Han Ding and Shaohua Zhang},
booktitle = {ICRA 2025},
year = {2025}
}