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Lessons in Putting Platform Tools into Practice for Radiologists

A tour de force delivers fundamentals in machine learning and AI

Society for Imaging Informatics in Medicine (SIIM) Announces CMIMI23 Program

The Society for Imaging Informatics in Medicine (SIIM) is planning its Conference on Machine Intelligence in Medical Imaging, SIIM CMIMI23, co-sponsored by American Association of Physicists in Medicine (AAPM), to be held in-person October 1-2, 2023 at Johns Hopkins in Baltimore, MD. 

AI Essentials in Radiology: Experts Weigh In

Leading radiologists offer insight into AI governance and clinical applications

Photo Gallery of Radiology Technology, Highlights from RSNA 2022

Radiology Leaders Earn Prestigious RSNA 2022 Gold Medals

The highest honor bestowed to members by RSNA, its Gold Medal, was awarded to three deserving radiologists during the 108th Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA 2022).

RSNA 2022 Day 4: Back to Basics on AI, ABUS Training, and ML in RO

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.

RSNA Announces Results of Brain Tumor AI Challenge

AI-based system could help triage brain MRIs

 E-Mail 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

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