Ultrasound (US) imaging is commonly employed for the diagnosis and staging of abdominal aortic aneurysms (AAA), mainly due to the non-invasiveness and high availability. High inter-operator variability and a lack of repeatability of current US image acquisition impairs the implementation of extensive screening programs for affected patient populations. However, this opens the way to a possible automation of the procedure, and recent works have exploited the use of robotic platforms for US applications, both in diagnostic and interventional scenarios. In this work, we propose a system for autonomous robotic US acquisitions aimed at the quantitative assessment of patients’ vessel diameter for abdominal aortic aneurysm screening. Using a probabilistic measure of the US quality, we introduce an automatic estimation of the optimal pressure to be applied during the acquisition, and an online optimization of the out-of-plane rotation of the US probe to maximize the visibility of the aorta. We evaluate our method on healthy volunteers and compare the results to manual acquisitions performed by a clinical expert, demonstrating the feasibility of the presented system for AAA screening.
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Ultrasound (US) imaging is commonly employed for the diagnosis and staging of abdominal aortic aneurysms (AAA), mainly due to the non-invasiveness and high availability. High inter-operator variability and a lack of repeatability of current US image acquisition impairs the implementation of extensive screening programs for affected patient populations. However, this opens the way to a possible automation of the procedure, and recent works have exploited the use of robotic platforms for US applic...
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