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Abstract #2028

A Single-Image Super-Resolution Method for Late Gadolinium Enhancement CMR

Jin Zhu1, Guang Yang2,3, Tom Wong2,3, Raad Mohiaddin 2,3, David Firmin2,3, Jennifer Keegan 2,3, and Pietro Lio1

1Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom, 2National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3Cardiovascular Research Centre, Royal Brompton Hospital, London, United Kingdom

3D late gadolinium enhanced (LGE) CMR is a useful imaging modality for detecting scar tissue in patients with atrial fibrillation. In order to visualize the thin-walled left atrium and scar tissue, high spatial resolution and contiguous coverage are required. However, increased spatial resolution requires markedly prolonged scanning time. In this paper, we propose a ROI focused single-image super-resolution (SISR) method based on the generative adversarial networks architecture to increase the apparent spatial resolution of 3D LGE data without increasing scan time. The proposed SISR method can boost the spatial resolution of the LGE CMR images while maintaining the perceptual quality.

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