New ultrasound methods that can be used to quantitatively assess liver fat content have
recently been developed. These quantitative ultrasound (QUS) methods are based on the …

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and
biological tissues. QUS techniques extract fundamental physical properties of tissues based …

Purpose The nonalcoholic fatty liver disease is the most common liver abnormality. Up to
date, liver biopsy is the reference standard for direct liver steatosis quantification in hepatic …

Nonalcoholic fatty liver disease is a major global health concern with increasing prevalence,
associated with obesity and metabolic syndrome. Recently, quantitative ultrasound-based …

Background Radiofrequency ultrasound data from the liver contain rich information about
liver microstructure and composition. Deep learning might exploit such information to assess …

In the world, nonalcoholic fatty liver disease (NAFLD) accounts for majority of diffuse hepatic
diseases. Notably, substantial liver fat accumulation can trigger and accelerate hepatic …

Background Quantitative US (QUS) using radiofrequency data analysis has been recently
introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may …

Objective To evaluate the use of ultrasound coupled with machine learning (ML) and deep
learning (DL) techniques for automated or semi-automated classification of myositis …

Background Advanced confounder-corrected chemical shift–encoded MRI-derived proton
density fat fraction (PDFF) is a leading parameter for fat fraction quantification in …

Nonalcoholic fatty liver disease (NAFLD) is believed to affect one-third of American adults.
Noninvasive methods that enable detection and monitoring of NAFLD have the potential for …