MRI Meets AI: How Artificial Intelligence is Enhancing Healthcare
Magnetic resonance imaging (MRI) has been a vital tool in healthcare for over four decades. With ongoing improvements to the technology, MRI scans have become even more reliable. One of the latest enhancements that has not yet been fully adopted is the use of artificial intelligence (AI) to improve the quality of scans and provide supportive tools for repetitive tasks associated with the MRI process. This article aims to explore how AI is changing MRI and its impact on healthcare.
Advancements in MRI
AI is making MRI an even more reliable diagnostic tool than it already is. MRI is often the last snapshot taken before a surgical procedure, providing the best level of detail. Cardiac MRIs, for example, can show cardiac chambers and outflow tracts from various angles, providing detail not seen on other scans. AI enhances efficacy and boosts efficiency for technologists, leading to faster diagnosis rates, including quicker cancer detection, and earlier intervention.
The Benefits of AI for MRI
From the radiology MRI technologist’s perspective, AI can be a welcome upgrade to traditional MRI equipment. AI can program scans that are optimized without the need for a specialist present. In radiologist reporting, AI can detect minuscule and early-stage cancerous nodules or lesions or quantify brain scans that detect and score disease, such as dementia and Alzheimer’s. Furthermore, AI can also assign a grade or value that helps with the diagnosis process. AI allows for shorter scans of 3-D images and can also upload images from an MRI scan to virtual reality (VR) software platforms, shortening the learning curve for these procedures.
Shorter Scan Times and Improved Image Quality
AI is able to shorten scan times by turning coarsely sampled, more rapid MRI scans into higher resolution images, minimizing the degradation from patient movement and reducing discomfort. Improvements in technology have led to larger, roomier MRI systems that can now be more efficiently upgraded with AI technology filters, powerful radiofrequency coils, and enhanced software programs, leading to quicker, more accurate scans.
Related Facts:
– AI technology is still in its early stages for this application and may require hardware upgrades, a capital expense for any imaging department or clinic.
– Studies by Stanford University in California show that using AI for MRI reconstruction can result in much faster imaging procedures, at half or even a quarter of the time previously required, while still rendering accurate images.
– VR can be used to further train medical students and surgical residents, using AI-collected data from MRI scans, and lessening the need for cadavers.
Key Takeaway:
Incorporating AI into MRI scans will lead to faster and more accurate scans, reducing patient discomfort and improving workflow, especially in busy hospitals. The technology is still in its early stages but holds a lot of promise for additional upgrades and potential applications.
Conclusion:
AI has the potential to revolutionize MRI in healthcare. Implementing AI in MRI scans can lead to shorter scan times while still providing accurate images. It can also reduce the need for human intervention and improve workflow, leading to faster diagnosis rates and earlier intervention. The use of VR in training medical students can also lead to improved outcomes. While there is still a long way to go, incorporating AI into MRI systems is a promising step forward to improving healthcare.
