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Self-Adaptive Ultrasound Scanning System for Imaging Human Spine

Jingyu Zhang, Tianjian Liu, Yunjiang Wang, Weiwei Jiang, Keji Yang, Haoran Jin, Yongjian Zhu

2021IEEE Transactions on Industrial Electronics24 citationsDOI

Abstract

Ultrasound imaging as a user-friendly and radiation-free navigation scheme has been gradually applied to minimally invasive spinal surgeries. However, acquiring an interpretable ultrasound image always requires experienced sonographers, which dramatically restricts its applications. To this end, in this article, a self-adaptive ultrasound scanning system (SAUSS) is proposed to image the human spine. This system automatically scans human back and real-time displays the spine structure. During scanning, our self-adaptive attitude-adjusting mechanism ensures the scan posture of the ultrasound probe, and guarantees human comfort and ultrasound coupling at the same time. According to the phantom experiments, our proposed system can maintain the resultant force in an appropriate region from 14 to 16 N on different segments of the spine and under different respiratory rates. Meanwhile, the automatically scanned image achieves higher quality and better repeatability than freehand one. In human trials, the image provided from SAUSS keeps clear image textures that are almost on par with computed tomography (CT) images, and its stability is also demonstrated from the comparisons of force fluctuations. In all, it has a great potential on navigation of spine surgery.

Topics & Concepts

Imaging phantomComputer visionUltrasoundComputer scienceArtificial intelligenceImage qualityUltrasound imagingBiomedical engineeringImage (mathematics)MedicineRadiologySoft Robotics and ApplicationsSurgical Simulation and TrainingUltrasound Imaging and Elastography
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