The development of medical applications of machine learning has required manual
annotation of data, often by medical experts. Yet, the availability of large-scale unannotated …

Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease
(NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its …

Background and objectives Non-alcoholic fatty liver disease (NAFLD) is a common liver
disease with a rapidly growing incidence worldwide. For prognostication and therapeutic …

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver
diseases (CLD) which can progress to liver cancer. The severity and treatment of NAFLD is …

To improve the understanding of the complex biological process underlying the
development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) …

This study aims to automatically detect the degree of pathological indices as a reference
method for detecting the severity and extent of various liver diseases from pathological …

Addressing the common challenges posed by limitations in medical images, our study
involved the collection of CT images from the abdominal area of patients. We meticulously …

This study introduces a liver fibrosis staging method based on the fusion of multi-modal
imaging features. By leveraging ultrasound gray-scale images and ultrasound shear wave …

Hepatic fibrosis is an important prognostic factor as severe liver fibrosis may lead to liver
cancer or even death. To grade liver fibrosis, ultrasound gray-scale images and ultrasound …

Segmentation and classification of anomalies is a critical problem in medical imaging.
Machine learning has demonstrated potential in automating this problem but generally relies …