arXiv 2003.072162020-03-18eess.IVcs.CVphysics.med-ph

Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients

University College London（伦敦大学学院）；University of Ibadan（伊巴丹大学）；Great Ormond Street Hospital for Children（大奥蒙德街儿童医院）；UCL Great Ormond Street Institute of Child Health（伦敦大学学院大奥蒙德街儿童健康研究所）；King’s College London（伦敦国王学院）；Microsoft Research Cambridge（微软剑桥研究院）；Department of Radiology, College of Medicine, University of Ibadan, Nigeria（伊巴丹大学医学院放射科）；Department of Paediatrics, College of Medicine, University of Ibadan, Nigeria（伊巴丹大学医学院儿科）；Centre for Medical Image Computing and Department of Computer Science, University College London, UK（伦敦大学学院医学影像计算中心和计算机科学系）；Department of Biomedical Engineering, King’s College London, UK（伦敦国王学院生物医学工程系）；Machine Intelligence and Perception Group, Microsoft Research Cambridge, UK（微软剑桥研究院机器智能与感知组）

Matteo Figini, Hongxiang Lin, Godwin Ogbole, Felice D Arco, Stefano B. Blumberg, David W. Carmichael, Ryutaro Tanno, Enrico Kaden, Biobele J. Brown, Ikeoluwa La… 展开作者

Matteo Figini, Hongxiang Lin, Godwin Ogbole, Felice D Arco, Stefano B. Blumberg, David W. Carmichael, Ryutaro Tanno, Enrico Kaden, Biobele J. Brown, Ikeoluwa Lagunju, Helen J. Cross, Delmiro Fernandez-Reyes, Daniel C. Alexander

备注：: 6 pages, 3 figures, accepted at ICLR 2020 workshop on Artificial Intelligence for Affordable Healthcare

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英文摘要：

1.5T or 3T scanners are the current standard for clinical MRI, but low-field (<1T) scanners are still common in many lower- and middle-income countries for reasons of cost and robustness to power failures. Compared to modern high-field scanners, low-field scanners provide images with lower signal-to-noise ratio at equivalent resolution, leaving practitioners to compensate by using large slice thickness and incomplete spatial coverage. Furthermore, the contrast between different types of brain tissue may be substantially reduced even at equal signal-to-noise ratio, which limits diagnostic value. Recently the paradigm of Image Quality Transfer has been applied to enhance 0.36T structural images aiming to approximate the resolution, spatial coverage, and contrast of typical 1.5T or 3T images. A variant of the neural network U-Net was trained using low-field images simulated from the publicly available 3T Human Connectome Project dataset. Here we present qualitative results from real and simulated clinical low-field brain images showing the potential value of IQT to enhance the clinical utility of readily accessible low-field MRIs in the management of epilepsy.

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