A review on automatic fetal and neonatal brain MRI segmentation
In recent years, a variety of segmentation methods have been proposed for automatic
delineation of the fetal and neonatal brain MRI. These methods aim to define regions of …
delineation of the fetal and neonatal brain MRI. These methods aim to define regions of …
Deep learning for retrospective motion correction in MRI: a comprehensive review
Motion represents one of the major challenges in magnetic resonance imaging (MRI). Since
the MR signal is acquired in frequency space, any motion of the imaged object leads to …
the MR signal is acquired in frequency space, any motion of the imaged object leads to …
The develo** human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction
Abstract The Develo** Human Connectome Project (dHCP) seeks to create the first 4-
dimensional connectome of early life. Understanding this connectome in detail may provide …
dimensional connectome of early life. Understanding this connectome in detail may provide …
A dedicated neonatal brain imaging system
EJ Hughes, T Winchman, F Padormo… - Magnetic resonance …, 2017 - Wiley Online Library
Purpose The goal of the Develo** Human Connectome Project is to acquire MRI in 1000
neonates to create a dynamic map of human brain connectivity during early development …
neonates to create a dynamic map of human brain connectivity during early development …
Multimodal surface matching with higher-order smoothness constraints
In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical
sensitivity and spatial localisation of group studies, and cortical surface-based alignment …
sensitivity and spatial localisation of group studies, and cortical surface-based alignment …
The develo** human connectome project neonatal data release
The Develo** Human Connectome Project has created a large open science resource
which provides researchers with data for investigating typical and atypical brain …
which provides researchers with data for investigating typical and atypical brain …
Network accelerated motion estimation and reduction (NAMER): convolutional neural network guided retrospective motion correction using a separable motion model
Purpose We introduce and validate a scalable retrospective motion correction technique for
brain imaging that incorporates a machine learning component into a model‐based motion …
brain imaging that incorporates a machine learning component into a model‐based motion …
Accelerated motion correction for MRI using score-based generative models
Magnetic Resonance Imaging (MRI) is a powerful medical imaging modality, but
unfortunately suffers from long scan times which, aside from increasing operational costs …
unfortunately suffers from long scan times which, aside from increasing operational costs …
Three‐dimensional motion corrected sensitivity encoding reconstruction for multi‐shot multi‐slice MRI: application to neonatal brain imaging
Purpose To introduce a methodology for the reconstruction of multi‐shot, multi‐slice
magnetic resonance imaging able to cope with both within‐plane and through‐plane rigid …
magnetic resonance imaging able to cope with both within‐plane and through‐plane rigid …
Retrospective motion correction in multishot MRI using generative adversarial network
Abstract Multishot Magnetic Resonance Imaging (MRI) is a promising data acquisition
technique that can produce a high-resolution image with relatively less data acquisition time …
technique that can produce a high-resolution image with relatively less data acquisition time …