Gadgetron Global Network and Intelligence Computing: Clinical Imaging Application Development and Software Infrastructure

National Heart, Lung, And Blood Institute

Investigators

Linked publications, trials & patents

Abstract

The past FY of 2021-2022 was successful for Gadgetron AI R&D. More AI applications were developed and deployed to clinical practice. Hui Xue, Jessica Artico, Rhodri H. Davies, Robert Adam, Abhishek Shetye, Joo B Augusto, Anish Bhuva, Fredrika Frjdh, Timothy C Wong, Miho Fukui, Joo L. Cavalcante, Thomas A Treibel, Charlotte Manisty, Marianna Fontana, Martin Ugander, James C. Moon, Erik B. Schelbert, Peter Kellman. Automated Inline Artificial Intelligence Measured Global Longitudinal Shortening and Mitral annular plane systolic excursion: Reproducibility and Prognostic Significance. Journal of the American Heart Association. 2022;0:e023849. https://doi.org/10.1161/JAHA.121.023849 Automated in-line myocardial segmentation of joint T1 and T2 mapping using deep learning. James Howard, Kelvin Chow, Liza Chacko, Mariana Fontana, Graham Cole, Peter Kellman, Hui Xue. Radiology: Artificial Intelligence, 2022 (in final revision). Azaan Rehman, Peter Kellman, Rhodri H Davies, Iain Pierce, Marianna Fontana, James C Moon, Hui Xue. Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging. Artificial Intelligence in Cardiovascular Magnetic Resonance Imaging - A Joint Summit of the EACVI and SCMR, 2022 (Best paper award). Peter Kellman, Hui Xue, Kelvin Chow, James Howard, Liza Chacko, Graham Cole, Marianna Fontana. Bright-blood and dark-blood phase sensitive inversion recovery late gadolinium enhancement and T1 and T2 maps in a single free-breathing scan: an all-in-one approach. Journal of Cardiovascular Magnetic Resonance, 23, 2021. Hui Xue, Jessica Artico, Marianna Fontana, James C Moon, Rhodri H Davies, Peter Kellman. Landmark detection in Cardiac Magnetic Resonance Imaging Using A Convolutional Neural Network. Radiology: Artificial Intelligence, Vol 3, 2021; https://doi.org/10.1148/ryai.2021200197. (Selected as the cover page story of this issue)