Transcranial Doppler analysis based on computer and artificial intelligence for acute cerebrovascular disease

Area of Science:

• Neurology
• Medical Imaging
• Biomedical Engineering

Background:

• Cerebrovascular disease causes significant morbidity and mortality due to impaired brain blood circulation.
• Transcranial Doppler (TCD) ultrasonography is a non-invasive diagnostic tool providing crucial hemodynamic information.
• Existing TCD methods offer valuable data but can be enhanced by advanced technologies.

Purpose of the Study:

• To review the development, principles, and applications of TCD ultrasonography.
• To introduce the role of Artificial Intelligence (AI) in medicine, particularly emergency medicine.
• To summarize AI applications and advantages in TCD ultrasonography for cerebrovascular disease diagnosis.

Main Methods:

• Review of TCD ultrasonography principles and clinical applications.
• Overview of AI development in medical and emergency fields.
• Detailed summary of AI integration with TCD, including BCI, signal processing, and robotic assistance.

Main Results:

• AI algorithms can classify and denoise TCD signals effectively.
• AI facilitates the creation of combined brain-computer interface (BCI) and TCD systems.
• Intelligent robots can assist physicians in performing TCD examinations.

Conclusions:

• AI significantly enhances TCD ultrasonography capabilities for diagnosing cerebrovascular diseases.
• AI integration offers improved accuracy, efficiency, and novel diagnostic approaches in TCD.
• Future prospects indicate a growing role for AI in advancing TCD technology and patient care.