"It's important to quantify exposure to ionizing radiation because it can cause cancer and birth defects and should be kept to a minimum, especially during pregnancy," said co-lead author Marilyn L. Kwan, PhD.
A deep learning model that simulates a clinician’s diagnostic process can accurately diagnose Alzheimer’s disease from cognitively normal patients, according to a study published July 16 in Neurocomputing.
“The CXR-risk score took as input the radiograph only. This was intended to prove a point—that a CNN can extract prognostic information embedded in the image, without any other demographic or clinical information,” wrote authors of a new study published in JAMA Network Open.
Breast cancer screening using digital breast tomosynthesis has risen rapidly in the United States, but that isn’t the case in all regions or across all institutions, according to a new study published in Current Problems in Diagnostic Radiology.
A deep neural network platform can help radiologists detect abdominal aortic aneurysms (AAAs) on CT images, and is especially helpful in clinically challenging cases, according to research presented at the SIIM annual conference.
A higher level of background parenchymal enhancement (BPE) measured during breast MRI is associated with the presence of breast cancer in women at high risk of breast cancer but not in women with average risk, according to a new study.
A recent study validating the 2017 version of the ultrasound Liver Imaging Reporting and Data System (US LI-RADS) for detecting hepatocellular carcinoma (HCC) identified a few limitations in its scoring.
The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) was originally created to improve patient management and avoid unnecessary fine needle aspiration biopsy in patients with thyroid nodules. However, its clinical use is still questioned.
Cardiac MRI can detect cocaine’s impact on the cardiovascular system and help differentiate between a wide range of heart diseases, according to a new literature review study published in Radiology: Cardiothoracic Imaging.