A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging

Understand

Staging of liver fibrosis is important in the diagnosis and treatment planning of patients suffering from liver diseases.

• Current deep learning-based methods using abdominal magnetic resonance imaging (MRI) usually take a sub-region of the liver as an input, which nevertheless could miss critical information.
• To explore richer representations, we formulate this task as a multi-view learning problem and employ multiple sub-regions of the liver.
• Previously, features or predictions are usually combined in an implicit manner, and uncertainty-aware methods have been proposed.