Details

Autor(en) / Beteiligte

• Christensen-Jeffries, Kirsten
• Brown, Jemma
• Harput, Sevan
• Zhang, Ge
• Zhu, Jiaqi
• Tang, Meng-Xing
• Dunsby, Christopher
• Eckersley, Robert J.

Titel

Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time

Ist Teil von

• IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2019-07, Vol.66 (7), p.1246-1254

Ort / Verlag

United States: IEEE

Erscheinungsjahr

2019

Link zum Volltext

• IEEE_Xplore

Quelle

IEL

Beschreibungen/Notizen

• A number of acoustic super-resolution techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit. A crucial aspect of all ultrasound (US) super-resolution (SR) methods using single microbubble localization is time-efficient detection of individual bubble signals. Due to the need for bubbles to circulate through the vasculature during acquisition, slow flows associated with the microcirculation limit the minimum acquisition time needed to obtain adequate spatial information. Here, a model is developed to investigate the combined effects of imaging parameters, bubble signal density, and vascular flow on SR image acquisition time. We find that the estimated minimum time needed for SR increases for slower blood velocities and greater resolution improvement. To improve SR from a resolution of <inline-formula> <tex-math notation="LaTeX">\lambda </tex-math></inline-formula>/10 to <inline-formula> <tex-math notation="LaTeX">\lambda </tex-math></inline-formula>/20 while imaging the microvasculature structure modeled here, the estimated minimum acquisition time increases by a factor of 14. The maximum useful imaging frame rate to provide new spatial information in each image is set by the bubble velocity at low blood flows (<150 mm/s for a depth of 5 cm) and by the acoustic wave velocity at higher bubble velocities. Furthermore, the image acquisition procedure, transmit frequency, localization precision, and desired super-resolved image contrast together determine the optimal acquisition time achievable for fixed flow velocity. Exploring the effects of both system parameters and details of the target vasculature can allow a better choice of acquisition settings and provide improved understanding of the completeness of SR information.