3D Ultrasound Image Acquisition and Diagnostic Analysis of the Common Carotid Artery with a Portable Robotic Device
Longyue Tan, Zhaokun Deng, Mingrui Hao, Pengcheng Zhang, Xilong Hou, Chen Chen, Xiaolin Gu, Xiao-Hu Zhou, Zeng-Guang Hou, Shuangyi Wang
Abstract
Ultrasound (US) imaging of the carotid artery (CA) is a non-invasive diagnostic tool widely used in the medical field to assess the condition of the carotid artery, thereby pre- dicting the risk of cardiovascular and cerebrovascular diseases. However, implementing this method in primary healthcare can be challenging due to the requirement for professionally trained sonographers. With the adoption of US robotic devices, the probe pose can be acquired while scanning, offering the possibility for 3D reconstruction and providing analyses that are not dependent on operator experience. This article introduces a method to semi-automatically acquire serialized US images of the common carotid artery (CCA). The method involves a specially designed robotic device built with a 6-RSU parallel mechanism, which is controlled according to robot pose, force sensor data and synchronous US images. To validate the images acquired, a method is proposed to segment the intima-media of CCA and calculate the intima-media thickness (IMT), which is a key indicator for cerebrovascular events prediction. After that, we propose an algorithm to reconstruct CCA into 3D voxel data with patient movement and cardiac cycle compensated, and a longitudinal view US image of CCA can be resliced from the voxel. The methods are tested on human subjects and the results indicate that the system and workflow can provide both quantitative and qualitative information of CCA for further diagnosis.