Synthetic Aperture Focusing for Multi-Covariate Imaging of Sub-Resolution Targets.

Journal Article (Journal Article)

Coherence-based imaging methods suffer from reduced image quality outside the depth of field for focused ultrasound transmissions. Synthetic aperture methods can extend the depth of field by coherently compounding time-delayed echo data from multiple transmit events. Recently, our group has presented the Multi-covariate Imaging of Sub-resolution Targets (MIST), an estimation-based method to image the statistical properties of diffuse targets. MIST has demonstrated improved image quality over conventional delay-and-sum, but like many coherence-based imaging methods, suffers from limited depth of field artifacts. This article applies synthetic aperture focusing to MIST, which is evaluated using focused, plane-wave, and diverging-wave transmit geometries. Synthetic aperture MIST is evaluated in simulation, phantom, and in vivo applications, demonstrating consistent improvements in contrast-to-noise ratio (CNR) over conventional dynamic receive MIST outside the transmit depth of field, with approximately equivalent results between synthetic transmit geometries. In vivo synthetic aperture MIST images demonstrated 16.8 dB and 16.6% improvements in contrast and CNR, respectively, over dynamic receive MIST images, as well as 17.4 dB and 32.3% improvements over synthetic aperture B-Mode. MIST performance is characterized in the space of plane-wave imaging, where the total plane-wave count is reduced through coarse angular sampling or total angular span. Simulation and experimental results indicate wide applicability of MIST to synthetic aperture imaging methods.

Full Text

Duke Authors

Cited Authors

  • Morgan, MR; Bottenus, N; Trahey, GE; Walker, WF

Published Date

  • June 2020

Published In

Volume / Issue

  • 67 / 6

Start / End Page

  • 1166 - 1177

PubMed ID

  • 31940530

Pubmed Central ID

  • PMC7337595

Electronic International Standard Serial Number (EISSN)

  • 1525-8955

International Standard Serial Number (ISSN)

  • 0885-3010

Digital Object Identifier (DOI)

  • 10.1109/tuffc.2020.2966116

Language

  • eng