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AI-based system could help triage brain MRIs


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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.
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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. ....

United States , Oak Brook , Bernardoc Bizzo , Romeuc Domingues , Romane Gauriau , Tiagoa Sanchez , Emersonl Gasparetto , Felipec Kitamura , Marciort Garcia , Charlese Kahn Jr , Katherinep Andriole , Fabiolabc Macruz , Leonardom Vedolin , Suelyf Ferraciolli , Women Hospital Center , University Of Pennsylvania , Perelman School Of Medicine , Radiological Society Of North America Inc , Massachusetts General Hospital , Hospital Center , Clinical Data Science , Deep Learning Based Model , Detecting Abnormalities , Preliminary Results , Multi Site Experience , Osvaldo Landi Junior ,

RSNA: AI-based System Could Help Triage Brain MRI Exams


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. ....

United States , Oak Brook , Bernardoc Bizzo , Romeuc Domingues , Romane Gauriau , Tiagoa Sanchez , Emersonl Gasparetto , Felipec Kitamura , Marciort Garcia , Charlese Kahn Jr , Katherinep Andriole , Fabiolabc Macruz , Leonardom Vedolin , Suelyf Ferraciolli , Women Hospital Center , University Of Pennsylvania , Perelman School Of Medicine , Radiological Society Of North America Inc , Massachusetts General Hospital , Hospital Center , Clinical Data Science , Deep Learning Based Model , Detecting Abnormalities , Preliminary Results , Multi Site Experience , Osvaldo Landi Junior ,