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Figure 1. A high-fidelity 3-D tractography of the left ventricle heart muscle fibers of a mouse from Amsterdam Ph.D. researcher Gustav Strijkers.
News | Cardiac Imaging | June 07, 2019
The Amsterdam University Medical Center has won MR Solutions’ Image of the Year 2019 award for the best molecular...
At #ACC.19, Siemens unveiled a version of its go.Top platform optimized for cardiovascular imaging. The newly packaged scanner can generate the data needed to do CT-based FFR (fractional flow reserve). Photo by Greg Freiherr
Feature | Cardiac Imaging | March 22, 2019 | By Greg Freiherr
Reflecting a trend toward the increased use of ...
SyncVision iFR Co-registration from Philips Healthcare maps iFR pressure readings onto angiogram. Results from an international study presented at #ACC19 show that pressure readings in coronary arteries may identify locations of stenoses remaining after cardiac cath interventions.
Feature | Cardiac Imaging | March 18, 2019 | By Greg Freiherr
As many as one in four patients who undergo cath lab interventions can benefit from a technology that identifies the
Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.
Feature | Cardiac Imaging | March 17, 2019 | By Greg Freiherr
Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical applica
WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography. Photo by Greg Freiherr
Feature | Cardiac Imaging | March 16, 2019 | By Greg Freiherr
Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in echoca
Podcast | Cardiac Imaging | March 12, 2019
How smart algorithms might reduce the burden of modern practice
Collage depicts broad applications in machine learning or deep learning (DL) that can be applied to advanced medical imaging technologies. Size of the liver and its fat fraction — 22 percent — (top middle in collage) can be quantified automatically using an algorithm developed by Dr. Albert Hsiao and his team at the University of California San Diego. This and other information that might be mined by DL algorithms from CT and MR images could help personalize patients’ treatment. Collage provided by Albert Hsiao
Feature | Cardiac Imaging | March 12, 2019 | By Greg Freiherr
Acquiring these data could change patient management
