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Abstract #4487

Motion Correction Resolved for MRI via Multi-Tasking: A Simultaneous Reconstruction and Registration Approach

Veronica Corona1, Noémie Debroux1, Angelica I. Aviles-Rivero2, Guy Williams3, Martin J. Graves4, Carole Le Guyader5, and Carola-Bibiane Schoenlieb1

1Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom, 2Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, United Kingdom, 3Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom, 4Cambridge University Hospitals, Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 5INSA Rouen, Laboratoire de Mathématiques, Normandie Université, Saint-Étienne-du-Rouvray, France

The prolonged time required to form an MR image continues to impose different challenges at both theoretical and clinical levels. With this motivation in mind, this work addresses a central topic in MRI, which is how to correct the motion problem, through a new multitask optimisation framework. The significance is that by tackling the reconstruction and registration tasks $$$-$$$ simultaneously and jointly $$$-$$$ one can exploit their strong correlation reducing error propagations and resulting in a significant motion correction. The clinical potentials of our approach are reflected in having higher image quality with fewer artefacts whilst keeping fine details. We evaluate our approach through a set of quantitative and qualitative experimental results.

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