The Imaging Technology News (ITN) editorial team offers a summary of key sessions from Nov. 30, day four of RSNA 2022, which represent member and patient care focused programming presented at the 108th Radiological Society of North America Scientific Assembly and Annual Meeting.
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IMAGE: Examples of axial FLAIR sequences from studies within dataset A. From left to right: a patient with a likely normal brain; a patient presenting an intraparenchymal hemorrhage within the right. view more
Credit: Radiological Society of North America
OAK BROOK, Ill. - An artificial intelligence-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a study published in
Radiology: Artificial Intelligence.
MRI produces detailed images of the brain that help radiologists diagnose various diseases and damage from events like a stroke or head injury. Its increasing use has led to an image overload that presents an urgent need for improved radiologic workflow. Automatic identification of abnormal findings in medical images offers a potential solution, enabling improved patient care and accelerated patient discharge.
RSNA: AI-based System Could Help Triage Brain MRI Exams
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An artificial intelligence-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a study published in Radiology: Artificial Intelligence.
There are an increasing number of MRIs that are performed, not only in the hospital but also for outpatients, so there is a real need to improve radiology workflow. One way of doing that is to automate some of the process and also help the radiologist prioritize the different exams. OAK BROOK, Ill. (PRWEB) April 21, 2021 An artificial intelligence-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a study published in Radiology: Artificial Intelligence.