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Abstract #1820

Evaluation of dynamic 2D-EPI acquisitions for fetal brain tracking with neural networks

Sara Neves Silva1, Irina Grigorescu2, Alena Uus2, Johannes Steinweg2, Maria Deprez2, Jo Hajnal2, Kuberan Pushparajah2, Jana Hutter2, and Enrico De Vita2
1Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2King's College London, London, United Kingdom


Fetal MRI and MRS are often compromised due to unpredictable fetal motion and commonly require multiple repetitions for diagnostic studies. To overcome these limitations, we are working towards developing a deep-learning based automatic MRI fetal motion tracking method. Our method uses, as input, rapid dynamic multi-echo 2D-EPI acquisitions and is based on a 3D U-Net for brain localisation and translational motion parameters estimation for brain tracking. The results show rapid low-resolution acquisitions contain sufficient information to allow automated fetal brain localisation. Our technique can be used to assess fetal movements and to build navigation systems for fetal MRI/MRS.

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