Zogala D. Artificial intelligence in medical imaging

Area of Science:

• * Rapid advancements in Artificial Intelligence (AI) are transforming diverse fields, including medical imaging.
• * AI applications span image acquisition, processing, augmentation, and interpretation within healthcare.

Background:

• * AI is increasingly utilized in medical imaging, offering capabilities beyond human perception, particularly in radiomics.
• * Despite commercial solutions, robust evidence for AI's positive healthcare impact is still developing.

Purpose of the Study:

• * To review the current applications and future potential of AI in medical imaging.
• * To identify the benefits, risks, and ethical considerations associated with AI integration in healthcare.

Main Methods:

• * Review of current AI applications in medical image acquisition, processing, and interpretation.
• * Analysis of AI's role in radiomics and advanced image analysis.
• * Discussion of challenges including data dependency, algorithmic transparency, and ethical implications.

Main Results:

• * AI currently serves an assistive role in medical imaging, with significant potential for future evolution.
• * Key limitations include reliance on computational power, data quality, annotation accuracy, and lack of algorithmic transparency.
• * Integration of AI introduces novel ethical and legislative challenges.

Conclusions:

• * AI is poised for increased implementation in medical imaging, offering advanced analytical capabilities.
• * Addressing data quality, transparency, and ethical concerns is crucial for realizing AI's full potential in healthcare.
• * Further validation and evidence generation are necessary to confirm AI's positive impact on patient outcomes.