Artificial intelligence-based ultrasound imaging technologies for hepatic diseases

Area of Science:

• Medical Imaging
• Artificial Intelligence
• Hepatology

Background:

• Ultrasound (US) is a key non-invasive tool for hepatic disease diagnosis and treatment.
• Artificial Intelligence (AI) offers data-driven decision support for clinical applications.
• Integrating AI with US can enhance diagnostic accuracy and treatment efficacy for liver conditions.

Purpose of the Study:

• To review the advancements in AI applications for US-based hepatic disease diagnosis and treatment.
• To highlight key areas where AI is impacting liver disease management using US imaging.
• To discuss the current state and future potential of AI in US for hepatology.

Main Methods:

• Review of current literature on AI and US in hepatic disease.
• Summarization of AI techniques applied to US image analysis for liver conditions.
• Categorization of applications including steatosis grading, fibrosis staging, and lesion detection.

Main Results:

• AI integration in US imaging shows promise for improved detection and evaluation of hepatic diseases.
• Specific applications include steatosis grading, fibrosis staging, and focal liver lesion detection.
• AI aids in predicting treatment response and optimizing clinical workflows.

Conclusions:

• The field of AI in US imaging for liver diseases is rapidly evolving.
• AI-powered US has the potential to significantly improve liver disease diagnosis, reduce costs, and optimize workflows.
• Future advancements in AI will further enhance the clinical utility of US in hepatology.