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Proceedings Paper

Improvements on USCT SAFT imaging by divergence compensation
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Paper Abstract

The use of Synthetic Aperture Focusing Technique (SAFT) for reflectivity ultrasound tomography has limita- tions due to the low signal-to-noise ratio. To overcome this fact in reflectivity ultrasound tomography, some studies have been showing improvements, propounding to take advantage of ultrasound transmission phenom- ena. Nevertheless, they do not take into account the characteristic divergence of ultrasound propagation. To contribute to a solution, we propose an improvement called weighted-SAFT, and test it with simulated media. In this study, the following were used: k-Wave toolbox for data generation on heterogeneous medium (sound speed, density, and attenuation); numerical phantoms with different combination, size, geometry, and location of the simulated objects; Fast Marching Method for phase aberration correction and time of flight, based on Refraction tomography, to calculated the SAFT weighting. The data set was generated using 192 simulated single-element transducers (1 MHz) uniformly distributed along the perimeter of a circular area. The SAFT reconstructions were made using the raw received signal and, separately, the envelope of the signal. SAFT-reconstructions using the signal envelope shows a diffuse appearance, and the edges of the objects in these regions can not be delimited. It is observed how the weighting SAFT leads to a more balanced distribution of intensity values throughout the image, partially compensating the ultrasound divergence effect and improving the image contrast.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography, 1131911 (16 March 2020); doi: 10.1117/12.2549799
Show Author Affiliations
Diego Armando Cardona Cardenas, Univ. de São Paulo (Brazil)
Sergio Shiguemi Furuie, Univ. de São Paulo (Brazil)


Published in SPIE Proceedings Vol. 11319:
Medical Imaging 2020: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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