0000000000398407
AUTHOR
Cristina Lenardi
A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia
Abstract Background The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model. Methods LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived…
Study of optical absorbance and MR relaxation of Fricke xylenol orange gel dosimeters
Abstract Studies on the optical absorbance spectra of Fricke xylenol orange gel dosimeters were performed, in the wavelength range from 300 nm to 800 nm, in order to highlight some particular characteristics that can affect the achievable precision. The spectra are different mainly due to the different types of xylenol orange that was used and to a lower extent due to the different gelling agents (agarose or gelatine). The characteristic of variation of absorbance spectra versus dose, however, are similar in the various cases and can explain some peculiarities, as apparent effects of dose threshold. Changes of spectral shapes appear over the time after irradiation. Magnetic resonance measur…