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The impact of mid lag spatial coherence parameters on coherent target detection
Author(s): Rebecca Jones; Siegfried Schlunk; Jaime Tierney; Ryan Hsi; Brett Byram
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Paper Abstract

Kidney stones are often poorly visualized with ultrasound despite the fact that they have a large impedance mismatch. In previous kidney stone studies conducted by our group, we demonstrated that the Mid-Lag Spatial Coherence (MLSC) beamforming method suppresses the incoherent background speckle while enhancing coherent scatterers. This allowed kidney stones to be highlighted. To study this approach in more detail Field-II simulations and in-house phantoms containing kidney stones were used to test the effectiveness of MLSC with different parameters. The number of lags used during beamforming and the brightness of the point target were altered. Then, the CNR, SNR, CR, and PSNR of the phantoms and simulations were compared. The CNR experienced little change between lag ranges, but the SNR and PSNR increased with the start lag. SNR increased by 12.9% ± 2.9% between the lowest and highest lag range while PSNR increased by 27.9% ± 4.6% between the lowest and highest lag range. CR did not change in a regular pattern but remained consistently higher than delay and sum beamforming. We also compare MLSC against short-lag spatial coherence (SLSC) and show that we also see improvements over this method including an increase of MLSC over SLSC ranging between 250% and 401% for PSNR and between 414% and 879% for CR.

Paper Details

Date Published: 15 March 2019
PDF: 7 pages
Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 109550S (15 March 2019); doi: 10.1117/12.2514118
Show Author Affiliations
Rebecca Jones, Vanderbilt Univ. (United States)
Siegfried Schlunk, Vanderbilt Univ. (United States)
Jaime Tierney, Vanderbilt Univ. (United States)
Ryan Hsi, Vanderbilt Univ. Medical Ctr. (United States)
Brett Byram, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 10955:
Medical Imaging 2019: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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