- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
AI-Enabled Lung Assessment Tool for Handheld Ultrasound Gets FDA Nod
The artificial intelligence (AI) powered Auto B-line Counter, which reportedly produces a B-line count from a six-second ultrasound clip, may facilitate more expedient and consistent assessment of abnormal lung function.
The Food and Drug Administration (FDA) has granted 510(k) clearance for the Auto B-line Counter (Butterfly Network), a handheld ultrasound tool that may help accelerate assessment of suspected lung function abnormality in patients with conditions ranging from chronic obstructive pulmonary disease (COPD) to COVID-19.
In contrast to traditional manual processes for counting B-lines from lung ultrasound scans, the Auto B-line Counter utilizes deep learning technology that can provide a B-line count from a six-second ultrasound clip, according to the Butterfly Network, the manufacturer of the modality.
Incorporating an instant percent counting technique, Butterfly Network said the algorithm for the Auto B-line Counter accounts for discrete B-lines as well as confluent B-lines by the percentage of occupied rib space.
“Our AI-enabled Auto B-line Counter empowers providers to assess lung conditions faster and with more confidence and in turn will aid in earlier detection, diagnosis, and treatment of cardiovascular diseases, a leading cause of death globally, taking nearly 18 million lives each year,” noted Jonathan Rothberg, Ph.D., the founder and interim chief executive officer of Butterfly Network.
Multicenter Study Shows Merits of AI-Powered Ultrasound Assessment for Detecting Ovarian Cancer
January 3rd 2025Adjunctive AI offered greater than seven percent increases in sensitivity, specificity, and accuracy for ultrasound detection of ovarian cancer in comparison to unassisted clinicians who lacked ultrasound expertise, according to findings from new international multicenter research.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
December 13th 2024New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.
