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Abstract #1022

Real-time automatic field-of-view adjustment in fetal MR scans using Gadgetron

Sara Neves Silva1, Jordina Aviles Verdera1, Raphaël Tomi-Tricot2,3, Radhouene Neji2,3, Thomas Wilkinson1, Valéry Ozenne4, Alexander Lewin5, Lisa Story1, Enrico De Vita2, Mary Rutherford1, Kuberan Pushparajah2, Jo Hajnal1, and Jana Hutter1
1Perinatal Imaging & Health, King's College London, London, United Kingdom, 2Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, 3MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, 4Université de Bordeaux, Bordeaux, France, 5Forschungszentrum Jülich, Jülich, Germany

Synopsis

Keywords: Motion Correction, FetusMRI provides an ideal tool for characterising fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion. To address this challenge, we are developing an intrinsically motion-robust deep-learning-based fetal MRI method to achieve real-time fetal head tracking and update the acquisition geometry prospectively. Our method uses Gadgetron for real-time reconstruction of the scans and a 3D UNet for fetal head position location and motion estimation. Real-time tracking and correction for functional fetal MRI was demonstrated both in controlled phantom setups and in fetal MRI cases.

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Keywords