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Deformable Slice-to-Volume Registration for Motion Correction of Fetal Body and Placenta MRI

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TLDR
A Deformable SVR (DSVR), a novel approach for non-rigid motion correction of fetal MRI based on a hierarchical deformable S VR scheme to allow high resolution reconstruction of the fetal body and placenta is proposed.
Abstract
In in-utero MRI, motion correction for fetal body and placenta poses a particular challenge due to the presence of local non-rigid transformations of organs caused by bending and stretching. The existing slice-to-volume registration (SVR) reconstruction methods are widely employed for motion correction of fetal brain that undergoes only rigid transformation. However, for reconstruction of fetal body and placenta, rigid registration cannot resolve the issue of misregistrations due to deformable motion, resulting in degradation of features in the reconstructed volume. We propose a Deformable SVR (DSVR), a novel approach for non-rigid motion correction of fetal MRI based on a hierarchical deformable SVR scheme to allow high resolution reconstruction of the fetal body and placenta. Additionally, a robust scheme for structure-based rejection of outliers minimises the impact of registration errors. The improved performance of DSVR in comparison to SVR and patch-to-volume registration (PVR) methods is quantitatively demonstrated in simulated experiments and 20 fetal MRI datasets from 28–31 weeks gestational age (GA) range with varying degree of motion corruption. In addition, we present qualitative evaluation of 100 fetal body cases from 20–34 weeks GA range.

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Citations
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Journal ArticleDOI

Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging

TL;DR: A new real-time image-based motion tracking method based on deep learning that learns to predict fetal motion directly from acquired images, based on a recurrent neural network that infers motion parameters from anatomical features extracted from sequences of acquired slices.
Journal ArticleDOI

Fetal body MRI and its application to fetal and neonatal treatment: an illustrative review

TL;DR: In this paper, a review of the current literature on the latest developments in antenatal imaging for diagnosis and prognostication of congenital anomalies is coupled with illustrative cases in true radiological planes with viewable three-dimensional video models that show the potential of post-acquisition reconstruction protocols.
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Antenatal thymus volumes in fetuses that delivered <32 weeks' gestation: An MRI pilot study.

TL;DR: To generate magnetic resonance imaging ‐derived fetal thymus volumes standardized for fetal weight, it is hoped that the presence of chorioamnionitis and funisitis at delivery with thymic volumes in utero in fetuses that subsequently deliver preterm birth will be correlated.
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APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation

TL;DR: In this paper, the authors proposed a fully automatic pipeline to predict the biological age and health of the placenta based on a free-breathing rapid (sub-30 second) T2* scan in two steps: automatic segmentation using a U-Net and a Gaussian process regression model to characterize placental maturation and health.
References
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Journal ArticleDOI

Image quality assessment: from error visibility to structural similarity

TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
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Nonrigid registration using free-form deformations: application to breast MR images

TL;DR: The results clearly indicate that the proposed nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.
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Reconstruction of fetal brain MRI with intensity matching and complete outlier removal.

TL;DR: This work proposes a new method for reconstruction of 3D fetal brain MRI from 2D slices that is interleaved with motion correction and shows excellent results for clinical and optimized data.
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Robust Super-Resolution Volume Reconstruction From Slice Acquisitions: Application to Fetal Brain MRI

TL;DR: A novel technique based on a slice acquisition model, which enables the reconstruction of a volumetric image from multiple-scan slice acquisitions and a robust M-estimation solution which minimizes a robust error norm function between the model-generated slices and the acquired slices are developed.
Journal ArticleDOI

Registration-based approach for reconstruction of high-resolution in utero fetal MR brain images.

TL;DR: Results indicate that this method promises a unique route to acquiring high-resolution MRI of the fetal brain in vivo allowing comparable quality to that of neonatal MRI.
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