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In a recent interview with Diagnostic Imaging, Eliad Josephson discussed key attributes of the HLTH USA conference, AI trends and an ongoing shift of emphasis on the development of predictive technologies with diagnostics at center stage.

The newly cleared Aview Aorta Metrics software reportedly offers automated segmentation of aortic regions and classification of aortic zones based on chest CT images.

Use of the AI-enabled slab technology from reconstructed DBT imaging led to a 7.4-second mean reduction in reading time in a new study involving 391 cases and 15 reviewing radiologists.

Catch up on the top AI-related news and research in radiology over the past month.

Are there certain strategies that facilitate an alter ego-esque laser focus undeterred by distraction?

Catch up on a variety of FDA news in radiology from the past week.

Catch up on the top radiology content of the past week.

In addition to providing higher SNRs in vascular structures and parenchymal organs than energy-integrating detector CT, photon-counting CT enabled an approximately 30 percent reduction in volume CT dose index (CTDIvol) for patients with obesity, according to a new study.

Facilitating enhanced 3D visualization of skeletal anatomy, the BoneEnhance machine learning module reportedly provides automated segmentation of bone and surrounding tissues for the Accuro XV ultrasound system.

The future of AI in radiology lies in its potential capability to forge connections and enhance efficiencies for enterprise-wide workflows.

In a new podcast episode, Joseph Cavallo, MD, MBA, offered his perspective on AI integration, potential efficiency gains, navigating post-deployment monitoring and how to incorporate AI literacy into radiology resident training.

The FFR-IQ software recently demonstrated a 92.2 percent sensitivity for non-invasive estimation of fractional flow reserve (FFRC) based on coronary CT angiography (CCTA) scans.

A Kaiser score > 5 with breast MRI demonstrated a 97 percent sensitivity and 87.9 percent specificity for predicting malignancy in patients with BI-RADS 0 or 4 presentations on mammography and breast ultrasound, according to a new study.