We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




AI Outperforms Radiologists in Detecting Tiny Brain Hemorrhages on CT Scans

By MedImaging International staff writers
Posted on 02 Jan 2020
Print article
Image: CT scans of the head (Photo courtesy of UC San Francisco)
Image: CT scans of the head (Photo courtesy of UC San Francisco)
Scientists at UC San Francisco (San Francisco, CA, USA) and UC Berkeley (Berkeley, CA, USA) have developed an algorithm that performed better than two out of four expert radiologists in finding tiny brain hemorrhages in head scans. The algorithm could help doctors treat patients with traumatic brain injuries (TBI), strokes and aneurysms.

Radiologists have to look at thousands of images each day, searching for tiny abnormalities that can signal life-threatening emergencies. Some spots may be on the order of 100 pixels in size, in a 3D stack of images containing over a million of them, and even expert radiologists sometimes miss them, with potentially grave consequences. However, radiologists could be much more efficient and accurate if artificial intelligence (AI) technology can pick out the images with significant abnormalities, so they can be examined more closely.

The algorithm developed the UCSF researchers took just one second to determine whether an entire head scan contained any signs of hemorrhage. It also traced the detailed outlines of the abnormalities it found – demonstrating their location within the brain’s 3D structure. The algorithm found some small abnormalities that the experts missed. It also noted their location within the brain, and classified them according to subtype, information that physicians need to determine the best treatment. Notably the algorithm provided all of this information with an acceptable level of false positives – minimizing the amount of time that physicians would need to spend reviewing its results. The radiology experts said the algorithm’s ability to find very small abnormalities and demonstrate their location in the brain was a substantial advance.

“The hemorrhage can be tiny and still be significant,” said Pratik Mukherjee, MD, PhD, professor of radiology at UCSF. “That’s what makes a radiologist’s job so hard, and that’s why these things occasionally get missed. If a patient has an aneurysm, and it’s starting to bleed, and you send them home, they can die."

Related Links:
UC San Francisco
UC Berkeley


X-Ray Illuminator
X-Ray Viewbox Illuminators
Digital X-Ray Detector Panel
Acuity G4
Ultrasound Imaging System
P12 Elite
Portable Color Doppler Ultrasound System
S5000

Print article

Channels

Radiography

view channel
Image: Samir F. Abboud, MD, chief of emergency radiology at Northwestern Medicine, and co-author of the study detailing the new generative AI tool for radiology (Photo courtesy of José M. Osorio/Northwestern Medicine)

AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds

Radiology is emerging as one of healthcare’s most pressing bottlenecks. By 2033, the U.S. could face a shortage of up to 42,000 radiologists, even as imaging volumes grow by 5% annually.... Read more

Nuclear Medicine

view channel
Image: The prostate cancer imaging study aims to reduce the need for biopsies (Photo courtesy of Shutterstock)

New Imaging Approach Could Reduce Need for Biopsies to Monitor Prostate Cancer

Prostate cancer is the second leading cause of cancer-related death among men in the United States. However, the majority of older men diagnosed with prostate cancer have slow-growing, low-risk forms of... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.