Development and Evaluation of Ultrasound Image Learning Pipelines for MASLD Risk Stratification
Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 30% of the general population. Ultrasound-based imaging, including B-mode imaging and shear wave elastography (SWE), is widely used for noninvasive fibrosis assessment; however, the role of deep learning-based ultrasound image learning for MASLD risk stratification remains insufficiently characterized. In this study, we developed and evaluated ultrasound image learning pipelines using B-mode and SWE images for fibrosis staging and identification of patients with at-risk metabolic dysfunction-associated steatohepatitis (MASH). A total of 250 ultrasound examinations, one exam per subject, were included. M...
| Authors | Guangyi Zhang, Xiaohong Wang, Eugene Cheah et al. |
|---|---|
| Primary category | eess.IV |
| Published | 3 September 2026 |
| Last updated at source | 3 September 2026 |
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