Over 1050 New Jersey Auctions End Tomorrow 06/14 - Bid Now

The future of AI in MR: Supporting clinical decisions

October 10, 2017
MRI
From the October 2017 issue of HealthCare Business News magazine

Eventually, emerging post-processing techniques will tap elements of AI and ML to combine MR’s rich anatomical data with information from other forms of imaging. This dynamic form of post-processing could, for example, potentially enhance the live fusion of ultrasound and MR for biopsy, which could potentially lead to more accurate lesion targeting and help avoid the treatment of critical structures.

One day, we may even see comprehensive mapping of patient anatomy using MR and other modalities to create a digital avatar of each patient. This digital copy, the ultimate extension of the personalized medicine philosophy, could simulate response to therapy, thereby sparing patients the physical, mental and financial rigors associated with ineffective treatment.

stats
DOTmed text ad

We repair MRI Coils, RF amplifiers, Gradient Amplifiers and Injectors.

MIT labs, experts in Multi-Vendor component level repair of: MRI Coils, RF amplifiers, Gradient Amplifiers Contrast Media Injectors. System repairs, sub-assembly repairs, component level repairs, refurbish/calibrate. info@mitlabsusa.com/+1 (305) 470-8013

stats

Regardless of the form AI takes, the goal will be the same: to make MR exams more efficient, accurate and consistent, ensuring more reliable results each time for each patient. Helping to realize this goal will be the essential human element that is the radiologist.

(This article examines the potential benefits of employing artificial intelligence in magnetic resonance imaging. As such, it references technology that is not currently available.)

About the author: Murat Gungor is vice president of Magnetic Resonance (MR) at Siemens Healthineers North America.

Back to HCB News

You Must Be Logged In To Post A Comment