Research Highlights

A population-based phenome-wide association study of cardiac and aortic structure and function Wenjia Bai et al. (2020) Nature Medicine volume 26, pages 1654–1662. DOI “My research is at the interface between machine learning and medical imaging. I am interested in medical image … Continued

SmartHeart comic released

At SmartHeart we are passionate about developing and applying AI methods to develop smarter MR scanners. The aim is to use AI to improve how quickly images are acquired, and to make the images better quality as well. AI tools … Continued

SmartHeart presenting at MICCAI 2019

Researchers from the SmartHeart project will present 9 papers at this year’s MICCAI conference in Shenzhen, China. The list of papers being presented is given below: Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction Wenjia Bai, Chen … Continued

SmartHeart presenting at ISMRM 2019

Jo Schlemper, a PhD Student supervised by Daniel Rueckert, is presenting his work on “decomposing AUTOMAP to Achieve Scalability and Enhance Performance” at the International Society for Magnetic Resonance in Medicine (ISMRM) 27th Annual Meeting & Exhibition in Montreal, Canada, … Continued

“AI in Cardiac Imaging” conference

  1 NOVEMBER 2018 | UPDATE THIS EVENT IS NOW FULLY BOOKED. IF YOU WOULD  LIKE TO BE ADDED TO THE WAITING LIST PLEASE CLICK ON THE “REGISTER” LINK AND FOLLOW THE INSTRUCTIONS THERE.   January 16, 2019 | London … Continued

SmartHeart researchers at CMR 2018

There was a strong SmartHeart presence at CMR 2018 in Barcelona last week. The focus on CMR2018 was on “Improving Clinical Value by Technical Advances”, emphasising the common goal of improving clinical outcomes in cardiovascular disease through innovation in basic … Continued

SmartHeart presenting at MICCAI 2017

SmartHeart researchers have 3 papers accepted at this year’s International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI) which will be held in Quebec in September.   Poster session Semi-Supervised Learning for Network-Based Cardiac MR Image Segmentation Wenjia … Continued