Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

We demonstrate that AI models can accurately segment liver tumors without the need for
manual annotation by using synthetic tumors in CT scans. Our synthetic tumors have two …

Deep learning has become a thriving force in the computer aided diagnosis of liver cancer,
as it solves extremely complicated challenges with high accuracy over time and facilitates …

Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study
develops an automatic diagnosis system for liver lesions using multiphase enhanced …

Simple Summary In this study, after conducting a comprehensive review of 1356 papers that
evaluated the diagnostic performance of deep learning (DL) methods based on medical …

Hepatocellular Carcinoma (HCC), the most common primary liver cancer, is a significant
contributor to worldwide cancer-related deaths. Various medical imaging techniques …

Abstract Background and Aim Hepatocellular carcinoma (HCC) diagnosis mainly relies on
its pathognomonic radiological profile, obviating the need for biopsy. The project of …

Simple Summary Patients with postoperative early recurrence of hepatocellular carcinoma
within 2 years are at high risk for poor prognosis, and identifying high-risk patients with …

Objectives Machine learning (ML) for medical imaging is emerging for several organs and
image modalities. Our objectives were to provide clinicians with an overview of this field by …

Hepatocellular carcinoma (HCC) is a unique cancer entity that can be noninvasively
diagnosed using imaging modalities without pathologic confirmation. In 2018, several major …