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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>
<jats:bold>Purpose</jats:bold>
</jats:title>
<jats:p>Robot-assisted systems offer an opportunity to support the diagnostic and therapeutic treatment of vascular diseases to reduce radiation exposure and support the limited medical staff in vascular medicine. In the diagnosis and follow-up care of vascular pathologies, Doppler ultrasound has become the preferred diagnostic tool. The study presents a robotic system for automatic Doppler ultrasound examinations of patients’ leg vessels.</jats:p>
</jats:sec><jats:sec>
<jats:title>
<jats:bold>Methods</jats:bold>
</jats:title>
<jats:p>The robotic system consists of a redundant 7 DoF serial manipulator, to which a 3D ultrasound probe is attached. A compliant control was employed, whereby the transducer was guided along the vessel with a defined contact force. Visual servoing was used to correct the position of the probe during the scan so that the vessel can always be properly visualized. To track the vessel’s position, methods based on template matching and Doppler sonography were used.</jats:p>
</jats:sec><jats:sec>
<jats:title>
<jats:bold>Results</jats:bold>
</jats:title>
<jats:p>Our system was able to successfully scan the femoral artery of seven volunteers automatically for a distance of 20 cm. In particular, our approach using Doppler ultrasound data showed high robustness and an accuracy of 10.7 (±3.1) px in determining the vessel’s position and thus outperformed our template matching approach, whereby an accuracy of 13.9 (±6.4) px was achieved.</jats:p>
</jats:sec><jats:sec>
<jats:title>
<jats:bold>Conclusions</jats:bold>
</jats:title>
<jats:p>The developed system enables automated robotic ultrasound examinations of vessels and thus represents an opportunity to reduce radiation exposure and staff workload. The integration of Doppler ultrasound improves the accuracy and robustness of vessel tracking, and could thus contribute to the realization of routine robotic vascular examinations and potential endovascular interventions.</jats:p>
</jats:sec>
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1000
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Hinweis
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DeepGreen-ID: 22762378b6474c3aaa33bd742faca68f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search) ;
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