Artificial intelligence for neuro MRI acquisition: a review.
Hongjia Yang1, Guanhua Wang2, Ziyu Li3
1School of Biomedical Engineering, Tsinghua University, Beijing, China.
Magma (New York, N.Y.)
|June 26, 2024
Summary
Artificial intelligence (AI) significantly improves magnetic resonance imaging (MRI) acquisition in neuroimaging, enhancing workflow efficiency and throughput. This review covers AI advancements, clinical impacts, and potential risks for optimized MRI scans.
Area of Science:
- Neuroimaging
- Medical Imaging Technology
- Artificial Intelligence
Background:
- Magnetic Resonance Imaging (MRI) acquisition workflow in neuroimaging faces challenges in efficiency and throughput.
- Advancements in Artificial Intelligence (AI) offer potential solutions to optimize MRI processes.
Purpose of the Study:
- To review recent progress in AI applications for neuroimaging MRI acquisition.
- To evaluate the impact of AI on workflow efficiency, throughput, and artifact correction.
- To identify key AI technologies and their clinical implications.
Main Methods:
- Comprehensive analysis of recent AI-based methods in neuro MRI acquisition.
- Focus on technological advances, clinical impact, and associated risks.
Main Results:
- AI algorithms demonstrate a substantial positive impact on MRI acquisition efficiency and throughput.
- Specific AI algorithms effectively optimize acquisition steps, leading to improved workflow efficiency.
- Reported improvements in overall MRI acquisition performance attributed to AI integration.
Conclusions:
- AI holds transformative potential for neuro MRI acquisition, offering significant technological and clinical benefits.
- Potential risks and challenges associated with AI integration require careful consideration.
- Future research should focus on mitigating risks and further enhancing AI's role in MRI acquisition.
