<p>Plane-wave imaging for ultrafast ultrasound, revolutionized by substantially enhancing frame rates, has paved the way for numerous applications in medical ultrasound. To improve spatial resolution and contrast, plane-wave compounding is typically utilized. Plane-wave compounding, referred to as plane-wave synthetic focusing (PW-SF) in this study, coherently sums the echoes from plane waves steered at multiple angles. To further improve the image quality and reduce the computational complexity for PW-SF, this study investigates the impact of plane-wave angle distributions and beamforming grids. Plane-wave angles with evenly selected in the radian space and in the sine of radian space, referred to as <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\theta\)</EquationSource> </InlineEquation>-even and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation>-even angles, respectively, are analytically derived. For the beamforming grids, we apply a plane-wave pixel-based synthetic focusing (PW-PBSF) approach, directly focusing echoes on display pixels, to achieve the optimal image quality in terms of resolution and computational complexity. From the simulation and phantom experiment, the largest improvement in lateral resolution was observed with PW-PBSF [0.16&#xa0;mm], which produced 0.29&#xa0;mm compared with 0.35&#xa0;mm for PW-SF-256, corresponding to approximately a 17% enhancement. The <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation>-even angle discretization approach also provided higher contrast, contrast-to-noise ratio (CNR), and generalized contrast-to-noise ratio (gCNR) values, measured as 5.72 dB, 1.54, and 0.841&#xa0;dB, respectively whereas <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\theta\)</EquationSource> </InlineEquation>-even yielded 5.58&#xa0;dB, 1.51, and 0.814. Consistent with the phantom findings, In vivo imaging of carotid artery also demonstrated that the PW-PBSF can provide improved resolution of plane-wave images without incurring redundant computational costs.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Investigation of ultrasound plane-wave imaging for optimal synthetic focusing

  • Doyoung Jang,
  • Jaebum Park,
  • Jae Hee Song,
  • Tai-kyong Song,
  • Heechul Yoon

摘要

Plane-wave imaging for ultrafast ultrasound, revolutionized by substantially enhancing frame rates, has paved the way for numerous applications in medical ultrasound. To improve spatial resolution and contrast, plane-wave compounding is typically utilized. Plane-wave compounding, referred to as plane-wave synthetic focusing (PW-SF) in this study, coherently sums the echoes from plane waves steered at multiple angles. To further improve the image quality and reduce the computational complexity for PW-SF, this study investigates the impact of plane-wave angle distributions and beamforming grids. Plane-wave angles with evenly selected in the radian space and in the sine of radian space, referred to as \(\theta\) -even and \(\alpha\) -even angles, respectively, are analytically derived. For the beamforming grids, we apply a plane-wave pixel-based synthetic focusing (PW-PBSF) approach, directly focusing echoes on display pixels, to achieve the optimal image quality in terms of resolution and computational complexity. From the simulation and phantom experiment, the largest improvement in lateral resolution was observed with PW-PBSF [0.16 mm], which produced 0.29 mm compared with 0.35 mm for PW-SF-256, corresponding to approximately a 17% enhancement. The \(\alpha\) -even angle discretization approach also provided higher contrast, contrast-to-noise ratio (CNR), and generalized contrast-to-noise ratio (gCNR) values, measured as 5.72 dB, 1.54, and 0.841 dB, respectively whereas \(\theta\) -even yielded 5.58 dB, 1.51, and 0.814. Consistent with the phantom findings, In vivo imaging of carotid artery also demonstrated that the PW-PBSF can provide improved resolution of plane-wave images without incurring redundant computational costs.