New ultrasound techniques. Present and future

Area of Science:

• Critical Care Medicine
• Medical Imaging
• Biomedical Engineering

Background:

• Ultrasound is vital for critically ill patients.
• AI integration in medical imaging is rapidly advancing.
• Need for improved accuracy and efficiency in bedside ultrasound.

Purpose of the Study:

• To highlight advancements in clinical ultrasound for critically ill patients.
• To demonstrate the role of AI in automating ultrasound interpretation and measurements.
• To showcase new software simplifying bedside ultrasound examinations.

Main Methods:

• Development of AI-powered software for automated image optimization and interpretation.
• Utilizing AI for cardiac structure identification, Doppler planimetry, and vessel size measurement.
• Application of 'auto strain' for automated ventricular function and volume calculation.

Main Results:

• AI significantly improves accuracy and efficiency in bedside ultrasound.
• Automated tools facilitate accurate examinations by less experienced professionals.
• Enhanced hemodynamic monitoring and ventricular function assessment through AI-driven parameters.

Conclusions:

• AI-driven ultrasound represents a significant advancement in critical care.
• Automated measurements and interpretation lead to more precise and faster patient monitoring.
• Future developments aim for continuous, non-invasive ultrasound monitoring solutions.