Offering a variety of AI features for streamlined workflow and enhanced visualization, the Acuson Origin ultrasound system also features the newly FDA-cleared AcuNav Lumos 4D ICE (intracardiac echocardiography) catheter.
The Food and Drug Administration (FDA) has granted 510(k) clearance for the Acuson Origin cardiovascular ultrasound system and the accompanying AcuNav Lumos 4D ICE (intracardiac echocardiography) catheter.
The Acuson Origin system reportedly bolsters workflow efficiency for transthoracic echocardiography (TTE) and transesophageal echocardiography (TEE) with over 5,600 artificial intelligence (AI) automated measurements, according to Siemens Healthineers, the manufacturer of the device.
AI Assist, one of the new TTE features for the Acuson Origin, provides automated positioning of color and spectral Doppler regions of interest. Offering real-time cardiac view recognition, Siemens Healthineers said the 4D HeartAI feature has a 98 percent accuracy for the identification and alignment of multiplanar reconstruction (MPR).
“With its advanced AI features and potential to enhance diagnostic accuracy as well as patient care, the Acuson Origin is positioned to reshape health care’s approach to cardiovascular imaging,” noted David Zollinger, the head of cardiovascular ultrasound at Siemens Healthineers.
Providing advanced imaging for complex heart procedures, Siemens Healthineers noted the AcuNav Lumos catheter promotes enhanced accuracy of anatomical assessments with MPR biplane imaging. The device’s real-time 4D color Doppler capabilities also facilitate improved leak detection, according to Siemens Healthineers.
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.
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 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.