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Maria Deprez

Researcher at King's College London

Publications -  65
Citations -  665

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

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Journal ArticleDOI

Maternal depression during pregnancy alters infant subcortical and midbrain volumes.

TL;DR: In this article, the authors examined the brain anatomy of infants born to clinically diagnosed mothers and found that infants exposed to maternal antenatal depression had significantly larger subcortical grey matter volumes and smaller midbrain volumes.
Book ChapterDOI

Dynamic field mapping and motion correction using interleaved double spin-echo diffusion MRI

TL;DR: A new approach is developed that breaks the traditional “one-volume, one-weighting” paradigm by interleaving low-b and high-b slices, and combine this with a reverse phase-encoded double-spin echo sequence to facilitate advanced analyses where conventional methods fail.
Posted Content

In utero diffusion MRI: challenges, advances, and applications

TL;DR: In this article, the authors highlight specific challenges, outline strategies to target them, and discuss two main applications: fetal brain connectomics and placental maturation, which are discussed in detail.
Journal ArticleDOI

Motion corrected fetal body magnetic resonance imaging provides reliable 3D lung volumes in normal and abnormal fetuses

TL;DR: To calculate 3D‐segmented total lung volume (TLV) in fetuses with thoracic anomalies using deformable slice‐to‐volume registration (DSVR) with comparison to 2D‐manual segmentation, and to establish a normogram of TLV calculated by DSVR in healthy control fetuses.
Posted ContentDOI

Higher order spherical harmonics reconstruction of fetal diffusion MRI with intensity correction

TL;DR: By applying constrained spherical deconvolution and whole brain tractography to reconstructed fetal dMRI, the proposed methodology facilitates detailed investigated of developing brain connectivity and microstructure in-utero.