Invited seminar | Ultrasound Biomedical Imaging: improve image quality by automatically optimizing parameters

Where and when

Bologna, Italy – January 20th, 2023

speaker: Chiara Razzetta
affiliation: Dipartimento di Matematica, Università di Genova / Esaote Group  
date: January 20th, 2023
venue: Bologna (Italy), Dipartimento di Matematica, Università di Bologna – Piazza di Porta San Donato 5

Ultrasound Biomedical Imaging: improve image quality by automatically optimizing parameters

abstract: Medical ultrasound is the most widely used non-invasive real-time imaging system: it exploits the ability of human tissues to reflect ultrasound signals. In detail, reflected ultrasound can be processed to obtain images and quantitative measurements of the physical properties of tissues. If we refer to all the imaging modalities that a common ultrasound apparatus can handle, their properties change in accordance with numerous structural and non-structural factors of the machine. More in detail, the Point Spread Function (PSF) turns out to be space variant and dependent on the acquisition geometry and probe that is used. In addition, for each mode and each probe there are many parameters that govern the goodness of the image (transmitted waveform, transmission frequency, number of active probe elements and so on). These parameters are historically chosen according to experience and must be selected each time the machine specifications change. Is it then possible to develop one or more methods to make an automatic estimate of all the parameters involved for any given mode? And, in particular, can we hope to optimize the parameters so that the PSF is as uniform as possible? We have tried to answer these questions by formulating a model and an associated optimization problem.

https://site.unibo.it/mathematical-image-analysis/en/seminars

The seminar will be held in the context of the Winter School is organized in the framework of UNAEuropa and the Cooperation Agreement between the University partners of the Program Erasmus+ 2021 − 27 KA1 Learning Mobility of Individuals.

 

Credits

featured photo: © Mme Mim, CC BY-SA 4.0 , via Wikimedia Commons

Last update 26 October 2023