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

• URL: http://arxiv.org/abs/2003.07216v2
• Date: Wed, 18 Mar 2020 19:52:52 GMT
• Title: Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients
• Authors: Matteo Figini (1), Hongxiang Lin (1), Godwin Ogbole (2), Felice D Arco (3), Stefano B. Blumberg (1), David W. Carmichael (4 and 5), Ryutaro Tanno (1 and 6), Enrico Kaden (1 and 4), Biobele J. Brown (7), Ikeoluwa Lagunju (7), Helen J. Cross (3 and 4), Delmiro Fernandez-Reyes (1 and 7), Daniel C. Alexander (1) ((1) Centre for Medical Image Computing and Department of Computer Science - University College London - UK, (2) Department of Radiology - College of Medicine - University of Ibadan - Nigeria, (3) Great Ormond Street Hospital for Children - London - UK, (4) UCL Great Ormond Street Institute of Child Health - London - UK, (5) Department of Biomedical Engineering - Kings College London - UK, (6) Machine Intelligence and Perception Group - Microsoft Research Cambridge - UK, (7) Department of Paediatrics - College of Medicine - University of Ibadan - Nigeria)
• Abstract summary: 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. Low-field scanners provide images with lower signal-to-noise ratio at equivalent resolution. Recent paradigm of Image Quality Transfer has been applied to enhance 0.36T structural images.
• Score: 1.8884732354822316
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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