Ultrasound scanners are extensively employed as diagnostic support tools due to their portability and ability to provide real-time images and quantitative measurements of physical tissue properties. In the last decades, image quality has increased significantly, but it is still highly dependent on several factors and a high number of imaging parameters, among which impulse shape and central frequency, transmission focal depth, apodization weights can be cited. This thesis deals with finding methods to automatically optimize some of the imaging parameters, with the aim of improving ultrasound image and tissue properties reconstruction. More specifically, we first proceed in formulating a computationally feasible transmission model that explicitly depends on the to-be-optimized imaging parameters, with a particular attention to linear probe case. Consequently, we devise an optimization approach that largely exploits the implemented parametric model allowing us to consider the delays as free variable thus increasing the number of possible energy patterns. We apply the method to Acoustic Radiation Force Imaging and find encouraging results for the optimization of parameters at the transmission step. Finally, we deal with the receiving step for standard B-mode imaging with the aim of extending the optimization method to a full image reconstruction. Since the computational costs of simulating an image are extremely high, making the optimization of the parameters a difficult and long procedure, we find a local approximation of the Point Spread Function model along depth. The performance of these methods is assessed via simulated experiments performed in different settings.

A study on modeling and optimization of biomedical ultrasound imaging

RAZZETTA, CHIARA
2024-05-03

Abstract

Ultrasound scanners are extensively employed as diagnostic support tools due to their portability and ability to provide real-time images and quantitative measurements of physical tissue properties. In the last decades, image quality has increased significantly, but it is still highly dependent on several factors and a high number of imaging parameters, among which impulse shape and central frequency, transmission focal depth, apodization weights can be cited. This thesis deals with finding methods to automatically optimize some of the imaging parameters, with the aim of improving ultrasound image and tissue properties reconstruction. More specifically, we first proceed in formulating a computationally feasible transmission model that explicitly depends on the to-be-optimized imaging parameters, with a particular attention to linear probe case. Consequently, we devise an optimization approach that largely exploits the implemented parametric model allowing us to consider the delays as free variable thus increasing the number of possible energy patterns. We apply the method to Acoustic Radiation Force Imaging and find encouraging results for the optimization of parameters at the transmission step. Finally, we deal with the receiving step for standard B-mode imaging with the aim of extending the optimization method to a full image reconstruction. Since the computational costs of simulating an image are extremely high, making the optimization of the parameters a difficult and long procedure, we find a local approximation of the Point Spread Function model along depth. The performance of these methods is assessed via simulated experiments performed in different settings.
3-mag-2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1172858
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