Abstract
The poor propagation of acoustic waves in air-filled tissues is a challenge for ultrasound imaging. The lung is composed of alveoli, which are tiny gas-filled sacs at the ends of the bronchioles, responsible for the exchange of oxygen and carbon dioxide between the air and the blood. The complex propagation phenomena in these tissues are translated into different image artefacts, and its mere appearance can be profited for diagnosing different diseases. In this work, we propose advanced beamforming using singular value decomposition and pulse codding methods for ultrasound imaging reconstruction, with the aim of providing quantitative and automatic methods to evaluate lung tissue. We have performed a total of 12 tests under the same conditions in a lung phantom. By comparing the different beamforming and compounding strategies, we observe that by using singular value decomposition beamformer aberrations can be mitigated. The results of this work open the possibility of retrieving valuable information from the microporous structure of lung tissue, allowing the use of quantitative ultrasound and automatic methods to evaluate lung tissue.
BibTeX citation
@inproceedings{SendraTEC2022,
author = {Josep Rodríguez-Sendra and Enrique M. González-Mateo and Noé Jiménez and Francisco Camarena},
booktitle = {Tecniacústica 2022: 53º Congreso Español de Acústica. XII Congreso Ibérico de Acústica. European Symposium on NVH in Electric Vehicles. Elche, Spain. 2-4 November},
doi = {http://www.sea-acustica.es/fileadmin/Elche22/ID-80.pdf},
editor = {Conference proceedings},
month = {11},
organization = {Sociedad Española de Acústica},
pages = {1151-1156},
series = {Oral},
title = {Singular value decomposition beamforming and pulse-coded excitation for lung ultrasound aberration correction},
url = {http://www.sea-acustica.es/fileadmin/Elche22/ID-80.pdf},
year = {2022}
}