Prototype of a low-cost 3D breast ultrasound imaging system

This work describes a setup of the new acquisition system for 3D ultrasound images (i.e. B-mode) for breast tomography. Since premature and precise breast lesions diagnoses turn out in treatment more efficient and save lives, we are looking for a more precise, less painful exams and dose reduction for the patient. Therefore, a low cost scanner mechanism was built aiming to accommodate breasts under water while patient is laid down on a bed in which a robotic arm guides the ultrasound probe to acquire 2D images. Then 3D image is reconstructed using the 2D images due to render the mammary volume searching for lesions. The low cost scanner was built using a regular ultrasound machine, linear probe and major controls made by an Arduino Uno. We compared the acquired phantom images with gold standard images for mammary tissues diagnostics, i.e. Computerized Tomography and Magnetic Resonance Images. This study was evaluated using a paraffin-gel and mineral oil control phantom. Results show that the provided module is convicting enough to be used in local hospital as the next step of this study

Towards real-time magnetomotive ultrasound imaging

Magnetomotive ultrasound (MMUS) imaging indirectly enables visualization of magnetic nanoparticles (MNPs) with ultrasound. An external time varying magnetic field displaces MNPs and thus their closest surrounding, the induced displacement is tracked in the US data and color-coded on B-mode images. However, images are currently processed offline, which is time consuming and precludes clinical use of MMUS. In this work, the previously proposed MMUS algorithm (DOI: TUFFC.2013.2591) is automated and implemented online on the ULA-OP scanner

Towards real-time magnetomotive ultrasound imaging

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