Deep learning, 3D imaging of arteries may modernize heart disease diagnosis
Silicon Valley-based Heartflow and medical imaging experts from the Imperial College London have announced a collaboration to develop a noninvasive method to detect coronary artery blockages by producing 3D images of the heart.
According to a recent news release from Imperial College London, Heartflow Analysis is a personalized 3D model that stimulates and analyzes blood flow, aiding in heart disease diagnosis. The new partnership between will combine Heartflow's 3D imaging technology and Imperial's imaging expertise to create learning algorithms that will produce more accurate 3D models.
“We are delighted to collaborate with the team at Imperial, who are globally recognized leaders in applying deep learning techniques to medical imaging," said John H. Stevens, MD, president and CEO of HeartFlow, in a prepared statement. “I have no doubt that the combined expertise of the HeartFlow and Imperial teams will help accelerate turning cutting-edge science into ground-breaking products that can positively impact in how patients with suspected heart disease are diagnosed and managed.”
The collaboration will be led by Ben Glocker, MD and Daniel Rueckert, PhD, from Imperial College London, and will require co-locating a HeartFlow team from Imperial’s Biomedical Image Analysis (BioMedIA) group.
A recent graduate from Dominican University (IL) with a bachelor’s in journalism, Melissa joined TriMed’s Chicago team in 2017 covering all aspects of health imaging. She’s a fan of singing and playing guitar, elephants, a good cup of tea, and her golden retriever Cooper.