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Abstract #2406

Integrating 3D distortion correction in 3D deformable slice-to-volume reconstruction of the whole uterus and pelvis for 0.55T T2w fetal MRI

Alena Uus1,2, Sarah McElroy1,3, Anthony Price1,4, Jordina Aviles Verdera1, Sara Neves Silva1, Simi Bansal1, Kamilah St Clair1, Maria Deprez2, Vanessa Kyriakopoulou1, Lisa Story1,5,6, Kathleen Colford1, Jana Hutter1,2,7, Mary A. Rutherford1, and Joseph V. Hajnal1,8
1Early life imaging research department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Biomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 3MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom, 4Medical Physics and Clinical Engineering, Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom, 5Department of Women and Children’s Health, King's College London, London, United Kingdom, 6Fetal Medicine Unit, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom, 7Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany, 8Imaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

Synopsis

Keywords: Fetal, Fetal

Motivation: There is a need for true 3D pelvimetry and volumetry measurements for fetal MRI but it is not currently feasible with using stacks that were processed using only 2D slice distortion correction.

Goal(s): Will 3D distortion correction affect measurements relevant to delivery mode prediction?

Approach: We integrate 3D distortion correction transformation into deformable slice-to-volume registration method to reconstruct 3D isotropic images of the uterus and pelvis from low resolution T2w stack of slices.

Results: The proposed pipeline is operational and improves validity of 3D pelvis and fetal measurements. However, more optimisation, testing and a phantom study are required.

Impact: This pipeline could be potentially useful for various projects working on analysis of 3D large ROI datasets.

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Abstract

Keywords