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
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Trained Radiologists Can Detect Breast Cancer in An Instant

By MedImaging International staff writers
Posted on 15 Sep 2016
Print article
Researchers at Brigham and Women's Hospital (BWH; Boston, AM, USA), the University of York (United Kingdom), and other institutions showed radiologists mammograms for half a second, and found that they could identify abnormal mammograms at better than chance levels. They further tested this ability through a series of four experiments to explore what signal may alert radiologists to the presence of a possible abnormality, in the hopes of using these insights to improve breast cancer screening and early detection.

They found that radiologist performance did not depend on detection of breaks in the normal symmetry of left and right breasts. Moreover, above-chance classification is possible using images from the normal breast of a patient, even when overt signs of cancer are present only in the other breast. They speculate that parts of the parenchyma that do not contain a lesion, or that are in the contralateral breast, confer an abnormal ‘gist’ that may be based on a widely distributed image statistic that is learned by experts. The study was published on August 29, 2016, in Proceedings of the National Academy of Sciences (PNAS).

“Radiologists can have ‘hunches’ after a first look at a mammogram. We found that these hunches are based on something real in the images. It's really striking that in the blink of an eye, an expert can pick up on something about that mammogram that indicates abnormality,” said senior author Jeremy Wolfe, PhD, director of the Visual Attention Laboratory at BWH. “Not only that, but they can detect something abnormal in the other breast, the breast that does not contain a lesion. Radiologists may be picking up on some sort of early, global signal of abnormality that is unknown to us at this point.”

According to the researchers, defining the signal that experienced radiologists are detecting could help researchers refine and improve computer-aided detection (CAD) systems that can aid in medical screening and could be incorporated into clinician training to improve detection rates. The researchers are also interested in exploring whether other medical image experts, such as dermatologists and pathologists, can use analogous signals.

Related Links:
Brigham and Women's Hospital
University of York
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
DR Flat Panel Detector
1500L
New
X-Ray QA Meter
Piranha CT
New
Digital Radiography Generator
meX+20BT lite

Print article

Channels

Ultrasound

view channel
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)

Largest Model Trained On Echocardiography Images Assesses Heart Structure and Function

Foundation models represent an exciting frontier in generative artificial intelligence (AI), yet many lack the specialized medical data needed to make them applicable in healthcare settings.... Read more

Nuclear Medicine

view channel
Image: The multi-spectral optoacoustic tomography (MSOT) machine generates images of biological tissues (Photo courtesy of University of Missouri)

New Imaging Technique Monitors Inflammation Disorders without Radiation Exposure

Imaging inflammation using traditional radiological techniques presents significant challenges, including radiation exposure, poor image quality, high costs, and invasive procedures. Now, new contrast... 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 © 2000-2024 Globetech Media. All rights reserved.