The Diagnostic Imaging AI (artificial intelligence) focus page provides information, videos, podcasts, and the latest news about product developments, trial results, screening guidelines, and protocol guidance that touch on the development and use of AI across the healthcare continuum.
August 29th 2025
The AI-powered cardiovascular ultrasound device reportedly offers enhanced spatial and contrast resolution as well as bolstered 4D imaging that enables improved evaluation of cardiac function for a wide range of patients.
Can Innovations with AI Help Address the Impact of Staffing Shortages on Radiology Workflow?
October 7th 2024While staffing shortages in radiology continue to persist after the COVID-19 pandemic, current and emerging innovations powered by artificial intelligence (AI) may help facilities navigate these challenges and mitigate rising costs of health care.
AI Mammography Platform Shows Promising Results for Detecting Subclinical Breast Cancer
October 3rd 2024Mean artificial intelligence (AI) scoring for breasts developing cancer was double that of contralateral breasts at initial biennial screening and was 16 times higher at the third biennial screening, according to a study involving over 116,000 women with no prior history of breast cancer.
Can AI Enhance CT Detection of Incidental Extrapulmonary Abnormalities and Prediction of Mortality?
September 18th 2024Emphasizing multi-structure segmentation and feature extraction from chest CT scans, an emerging AI model demonstrated an approximately 70 percent AUC for predicting significant incidental extrapulmonary findings as well as two-year and 10-year all-cause mortality.
Can Radiomics and Autoencoders Enhance Real-Time Ultrasound Detection of Breast Cancer?
September 10th 2024Developed with breast ultrasound data from nearly 1,200 women, a model with mixed radiomic and autoencoder features had a 90 percent AUC for diagnosing breast cancer, according to new research.
Study Assesses Lung CT-Based AI Models for Predicting Interstitial Lung Abnormality
September 6th 2024A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.
What a Prospective CT Study Reveals About Adjunctive AI for Triage of Intracranial Hemorrhages
September 4th 2024Adjunctive AI showed no difference in accuracy than unassisted radiologists for intracranial hemorrhage (ICH) detection and had a slightly longer mean report turnaround time for ICH-positive cases, according to newly published prospective research.
FDA Expands Clearance of MRI-Guided AI Platform for Deep Brain Stimulation and Lesioning Techniques
September 3rd 2024Utilizing a new machine learning model, the OptimMRI software may improve radiosurgery applications and lesioning techniques such as MRI-guided focused ultrasound through enhanced targeting of the inferolateral part of the ventral intermediate nucleus (VIM).
Mammography Study: Can Stand-Alone AI Enhance Detection of Interval Breast Cancer?
August 28th 2024Identifying over 23 percent of interval breast cancers with a 96 percent sensitivity in mammography interpretation, an emerging AI software also facilitated correct localization in over 75 percent of cases involving interval breast cancer, according to new research.
FDA Clears Emerging Cardiovascular Point-of-Care Ultrasound Platform
August 22nd 2024Combining four CAD modules for valvular pathologies with a variety of automated measurements, the AI-enabled AISAP Cardio ultrasound system reportedly facilitates up to a 90 percent accuracy rate in detecting common cardiac conditions.
FDA Clears Updated AI Software for CT-Based Coronary Artery Calcium Assessment
August 22nd 2024Key features of the HealthCCSng V2.0 software include numerical coronary artery calcium (CAC) scoring, a new zero CAC category and user customization of upper and lower limits for CAC scoring categories.
What New Research Reveals About Deep Learning and CT Angiography Detection of Cerebral Aneurysms
August 21st 2024Providing an 85.7 percent sensitivity rate for detecting cerebral aneurysms on computed tomography angiography (CTA), the deep learning model also offered a similar AUC (93 percent) in comparison to radiology reports (91 percent).