Technology

Employing the SwiftMR software with deep learning reconstruction solutions from original equipment manufacturers (OEMs) may provide additional sequence coverage as well as scan time reduction.

In recent interviews with Diagnostic Imaging, Andrew Del Gaizo, MD, Nick Galante, MD and Marc Succi, MD, shared their perspective on the recent comment from NYC Health and Hospitals CEO Mitchell Katz, MD, about potentially replacing radiologists with AI.

In a recent interview, Marc Succi, MD, discussed findings from a new study examining the clinical reasoning capabilities of 21 large language models (LLMs), including GPT-5, Grok 4 and Claude 4.5 Opus.

In the latest episode of her “Breast Imaging in Focus” series, Manisha Bahl, MD, discusses key findings from a new study looking at partially autonomous AI-supported screening with mammography and digital breast tomosynthesis (DBT).

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

In a recent interview, Lior Fisher, MD, discussed new research findings for AI software that may enable single view ultrasound detection of valvular and ventricular dysfunction by non-cardiologists.

The neuropacs™ MRI-based AI software provided a 96 percent or better AUROC for differentiating between Parkinson’s disease, atypical parkinsonism, multiple system atrophy Parkinsonian variant and progressive supranuclear palsy, according to a prospective multicenter study published in JAMA Neurology.

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

The CT-based True Definition DL software reportedly facilitates enhanced efficiency and high-resolution visualization for musculoskeletal, pulmonary and inner ear imaging.

In a recent interview, Joseph Cavallo, MD, and Marla Sammer, MD, discussed the dearth of AI applications for pediatric imaging, new research evaluating adjunctive AI triage for CT detection of intracranial hemorrhages in children six and older, and going beyond the data points to ascertain the impact of AI on patient care.

Reportedly trained on over 21 million images, Butterfly Network’s AI-enabled Gestational Age tool reportedly provides reliable automated age assessments between 16 and 37 weeks.

Catch up on the most-well viewed radiology content in March 2026.

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

Catch up on a variety of new FDA clearances and approvals in radiology from the past week.

Providing automated tracking and image guidance of the Edwards PASCAL Ace mitral valve repair device, the DeviceGuide reportedly enables integration of live ultrasound and X-ray images into a single view.

The DeepEcho Blind Sweep Platform reportedly automates a variety of key prenatal ultrasound measurements including fetal heart rate, placental location and gestational age.

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

Only 41 percent of radiologists spotted radiographs that were generated by the large language model GPT-4o, according to newly published research.

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

New study findings demonstrate that the deep learning software syngo.CT Brain Hemorrhage VB60 reportedly offers a 93.6 percent sensitivity as well as 99.2 percent negative predictive value for intracranial hemorrhage.

Use of an MRI-based deep learning model also led to a greater than 33 percent increase in detecting brain metastases less than or equal to 3 mm, according to newly published research.

In the second part of a two-part interview, David Larson, M.D., M.B.A, and Jason Poff, M.D., shared their insights on the recent study of a structured pre-deployment approach to assessing AI models and potential directions in future radiology research.

Catch up on a variety of new FDA clearances and approvals in radiology from the past week.

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

In the first of a two-part interview, David Larson, M.D., M.B.A., and Jason Poff, M.D., discussed a new study examining the use of a structured pre-deployment method for evaluating the value of a portfolio of AI models for radiology.