Towards real-time magnetomotive ultrasound imaging

Maria Evertsson, Alessandro Ramalli, Theo Z. Pavan, Luciana C. Cabrelli, Roger Andersson, Magnus Cinthio, Piero Tortoli, Tomas Jansson

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review


Enabling detection of nanoparticles with ultrasound can open new application avenues for the ultrasound technique. Magnetomotive ultrasound (MMUS) is a technique under development which indirectly visualizes magnetic nanoparticles. In MMUS, an external time-varying magnetic field acts to displace the nanoparticles, and thus their closest surrounding. This induced displacement is subsequently detected and the nanoparticle location may then be revealed. The MMUS technique has shown to be promising in both phantom and animal studies but limited efforts have been made on optimizing the technique for clinical applications in the sense of providing real-time bedside imaging. In this work, the previously proposed MMUS algorithm is automated and implemented online on the ULA-OP scanner. To evaluate the online implementation, a phantom made of styrene-ethylene/butylene-styrene and mineral oil with a 2 % magnetic ferrite particle inclusion was used. MMUS displacement was calculated in the entire image area, 192×230 pixels, and in a sub-region of 130×90 pixels, covering the inclusion. It was found that the automated online implementation computes one full MMUS image in 2.8 seconds and the sub-region in 1.17 seconds, which should be compared to 1-2 minutes in post processing mode. An immediate on-screen change in the magnetomotive displacement could be observed as the applied magnetic field was altered.

Titel på värdpublikation2017 IEEE International Ultrasonics Symposium, IUS 2017
FörlagIEEE Computer Society
ISBN (elektroniskt)9781538633830
StatusPublished - 2017 okt. 31
Evenemang2017 IEEE International Ultrasonics Symposium, IUS 2017 - Washington, USA
Varaktighet: 2017 sep. 62017 sep. 9


Konferens2017 IEEE International Ultrasonics Symposium, IUS 2017

Ämnesklassifikation (UKÄ)

  • Medicinsk bildbehandling


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