Dr. Khashayar Rafatzand Profile

Dr. Khashayar Rafatzand

at Univ of Massachusetts Chan Medical School

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Proceedings Article | 16 March 2020 Paper

Feasibility of robot-assisted ultrasound imaging with force feedback for assessment of thyroid diseases

Jakub Kaminski, Khashayar Rafatzand, Haichong Zhang

Proceedings Volume 11315, 113151D (2020) https://doi.org/10.1117/12.2551118

KEYWORDS: Ultrasonography, 3D image processing, Robotics, Image processing, Data acquisition, Image registration

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Medical ultrasound is extensively used to define tissue textures and to characterize lesions, and it is the modality of choice for detection and follow-up assessment of thyroid diseases. Classical medical ultrasound procedures are performed manually by an occupational operator with a hand-held ultrasound probe. These procedures require high physical and cognitive burden and yield clinical results that are highly operator-dependent, therefore frequently diminishing trust in ultrasound imaging data accuracy in repetitive assessment. A robotic ultrasound procedure, on the other hand, is an emerging paradigm integrating a robotic arm with an ultrasound probe. It achieves an automated or semi-automated ultrasound scanning by controlling the scanning trajectory, region of interest, and the contact force. Therefore, the scanning becomes more informative and comparable in subsequent examinations over a long-time span. In this work, we present a technique for allowing operators to reproduce reliably comparable ultrasound images with the combination of predefined trajectory execution and real-time force feedback control. The platform utilized features a 7-axis robotic arm capable of 6-DoF force-torque sensing and a linear-array ultrasound probe. The measured forces and torques affecting the probe are used to adaptively modify the predefined trajectory during autonomously performed examinations and probe-phantom interaction force accuracy is evaluated. In parallel, by processing and combining ultrasound B-Mode images with probe spatial information, structural features can be extracted from the scanning volume through a 3D scan. The validation was performed on a tissue-mimicking phantom containing thyroid features, and we successfully demonstrated high image registration accuracy between multiple trials.

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