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Author

Maria Deprez

Other affiliations: St Thomas' Hospital
Bio: Maria Deprez is an academic researcher from King's College London. The author has contributed to research in topics: Diffusion MRI & Medicine. The author has an hindex of 11, co-authored 50 publications receiving 327 citations. Previous affiliations of Maria Deprez include St Thomas' Hospital.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: The combination of prenatal MRI with novel, motion-corrected 3D image registration software, as an adjunct to fetal echocardiography in the diagnosis of congenital heart disease provides safe, powerful, and highly complementary imaging of the fetal cardiovascular system.

83 citations

Journal ArticleDOI
TL;DR: 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.

55 citations

Journal ArticleDOI
TL;DR: In this paper, the authors developed a reconstruction method for scattered slice multi-shell high angular resolution diffusion imaging (HARDI) data, jointly estimating an uncorrupted data representation and motion parameters at the slice or multiband excitation level.

37 citations

Posted Content
08 May 2019
TL;DR: A slice-to-volume reconstruction framework for multi-shell HARDI data is introduced based on a data-driven representation as spherical harmonics and radial decomposition (SHARD) and results show robust reconstruction in severely motion-corrupted scans.
Abstract: Highlights • Subject motion in dMRI leads to a set of scattered slices with unique contrast.• We introduce a slice-to-volume reconstruction framework for multi-shell HARDI data• Based on a data-driven representation as spherical harmonics and radial decomposition (SHARD).• The method is evaluated in test-retest scans and in the neonatal dHCP cohort.• Results show robust reconstruction in severely motion-corrupted scans.

32 citations


Cited by
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Journal ArticleDOI
TL;DR: The methods used to create unbiased, age-appropriate MRI atlas templates for pediatric studies that represent the average anatomy for the age range of 4.5-18.5 years are presented, while maintaining a high level of anatomical detail and contrast.

1,756 citations

Journal ArticleDOI
TL;DR: The results suggest that the SRI24 atlas, although based on 3T MR data, allows equally accurate spatial normalization of data acquired at 1.5T as the comparison atlases, all of which are based on 1.
Abstract: This article describes the SRI24 atlas, a new standard reference system of normal human brain anatomy, that was created using template-free population registration of high-resolution magnetic resonance images acquired at 3T in a group of 24 normal control subjects. The atlas comprises anatomical channels (T1, T2, and proton density weighted), diffusion-related channels (fractional anisotropy, mean diffusivity, longitudinal diffusivity, mean diffusion-weighted image), tissue channels (CSF probability, gray matter probability, white matter probability, tissue labels), and two cortical parcellation maps. The SRI24 atlas enables multichannel atlas-to-subject image registration. It is uniquely versatile in that it is equally suited for the two fundamentally different atlas applications: label propagation and spatial normalization. Label propagation, herein demonstrated using diffusion tensor image fiber tracking, is enabled by the increased sharpness of the SRI24 atlas compared with other available atlases. Spatial normalization, herein demonstrated using data from a young-old group comparison study, is enabled by its unbiased average population shape property. For both propagation and normalization, we also report the results of quantitative comparisons with seven other published atlases: Colin27, MNI152, ICBM452 (warp5 and air12), and LPBA40 (SPM5, FLIRT, AIR). Our results suggest that the SRI24 atlas, although based on 3T MR data, allows equally accurate spatial normalization of data acquired at 1.5T as the comparison atlases, all of which are based on 1.5T data. Furthermore, the SRI24 atlas is as suitable for label propagation as the comparison atlases and detailed enough to allow delineation of anatomical structures for this purpose directly in the atlas.

371 citations

Book Chapter
01 Jan 2005
TL;DR: A novel deformable registration algorithm for diffusion tensor MR images that enables explicit optimization of tensor reorientation and improves the alignment of several major white matter structures examined.
Abstract: In this paper we present a novel deformable registration algorithm for diffusion tensor (DT) MR images that enables explicit analytic optimization of tensor reorientation. The optimization seeks a piecewise affine transformation that divides the image domain into uniform regions and transforms each of them affinely. The objective function captures both the image similarity and the smoothness of the transformation across region boundaries. The image similarity enables explicit orientation optimization by incorporating tensor reorientation, which is necessary for warping DT images. The objective function is formulated in a way that allows explicit implementation of analytic derivatives to drive fast and accurate optimization using the conjugate gradient method. The optimal transformation is hierarchically refined in a subdivision framework. A comparison with affine registration for inter-subject normalization of 8 subjects shows that our algorithm improves the alignment of manually segmented white matter structures (corpus callosum and cortio-spinal tracts).

314 citations

Journal ArticleDOI
TL;DR: The significance of future controlled studies should be judged based on their explanatory powers; that is, how well do they relate to brain growth abnormalities and/or provide useful clinicopathological correlates.
Abstract: Most researchers agree that autism spectrum disorders (ASD) comprise a group of developmental conditions whose pathological substratum resides in the brain. Despite the significance of neuropathological research in ASD, relatively few studies have been performed on the subject. The limited number of studies may be accounted, in part, by the scarcity of available tissues in different brain banks. Furthermore, variability within each patient population in regards to pre-agonal/agonal conditions, medications, comorbidity (e.g., seizures), and postmortem interval may all account for dissimilar findings among the limited number of reported studies. Only recently has a clear picture begun to emerge as to the neuropathological underpinnings of ASD. The presence of heterotopias, laminar effacement, and minicolumnopathy suggest that heterochronic divisions of periventricular germinal cells may provide for the asynchronous development of pyramidal cells and interneurons within the cerebral cortex. A similar defect within the rhombic lip may help explain brainstem and cerebellar malformations. Autism spectrum disorders are multifactorial conditions wherein a genetic proclivity and environmental stressors act at particular times during brain development to provide an autistic phenotype.

241 citations