A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Filters
iBEAT: A Toolbox for Infant Brain Magnetic Resonance Image Processing
2012
Neuroinformatics
We have developed an Infant Brain Extraction and Analysis Toolbox (iBEAT) for various processing of magnetic resonance (MR) images of infant brains. ...
Moreover, it can process not only single-time-point images for cross-sectional studies, but also multiple-time-point images of the same infant for longitudinal studies. ...
Magnetic resonance imaging (MRI) provides a safe way for in vivo assessments of brain tissues, and is thus widely used in many clinical and neuroscience studies on infant brain development. ...
doi:10.1007/s12021-012-9164-z
pmid:23055044
fatcat:7fbxuzcyqfbt7ftaueoos34nhq
Impacts of skull stripping on construction of three-dimensional T1-weighted imaging-based brain structural network in full-term neonates
2020
BioMedical Engineering OnLine
Skull stripping remains a challenge for neonatal brain MR image analysis. ...
This paper therefore aimed to clarify this issue by comparing two automatic (FMRIB Software Library's Brain Extraction Tool, BET; Infant Brain Extraction and Analysis Toolbox, iBEAT) and a semiautomatic ...
Hongxia Song and Gailian Li from the Neonatology Department for preparing and monitoring the neonates before and during imaging. ...
doi:10.1186/s12938-020-00785-0
pmid:32493402
fatcat:42cjucvwmzbebhixsx2skymiwu
A Novel Approach for Manual Segmentation of the Amygdala and Hippocampus in Neonate MRI
2019
Frontiers in Neuroscience
Neonate magnetic resonance (MR) images have different contrasts compared to adult images, and automated segmentation of brain magnetic resonance imaging (MRI) can thus be considered challenging as less ...
In conclusion, there is a clear need to improve and develop the procedures for automated segmentation of infant brain MR images. ...
University Foundation (JT), the Emil Aaltonen Foundation (JT), the Sigrid Juselius Foundation (HM), the Brain and Behavior Research Foundation YI Grant #1956 (LK), the Jane and Aatos Erkon Foundation ( ...
doi:10.3389/fnins.2019.01025
pmid:31616245
pmcid:PMC6768976
fatcat:p72mtm74xbcnhpqgncfdn7x34i
Deep Learning-Based Studies on Pediatric Brain Tumors Imaging: Narrative Review of Techniques and Challenges
2021
Brain Sciences
resonance imaging MRI / computed tomography CT) findings. ...
The purpose of this review paper is to include a detailed summary by first providing a succinct guide to the types of pediatric brain tumors and pediatric brain tumor imaging techniques. ...
Magnetic resonance imaging MRI, is the standard imaging technique for the sis of brain tumors [6, 7] . ...
doi:10.3390/brainsci11060716
pmid:34071202
fatcat:usmduuhzyzcsrh7lgto3ejzbfu
Myelin contributes to microstructural growth in human sensory cortex during early infancy
[article]
2021
bioRxiv
pre-print
The infant brain undergoes rapid physical changes after birth. However, how cortex develops remains unknown. ...
These data suggest a rethinking of developmental hypotheses and highlight the significance of cortical myelination in the development of brain function. ...
of the infant brains and Caitlyn Estrada for her contribution to data collection. ...
doi:10.1101/2021.03.16.435703
fatcat:oxqwwgdg6rgajanytcpcctadim
A fast stochastic framework for automatic MR brain images segmentation
2017
PLoS ONE
This paper introduces a new framework for the segmentation of different brain structures (white matter, gray matter, and cerebrospinal fluid) from 3D MR brain images at different life stages. ...
To accurately account for the large inhomogeneity in infant MRIs, a higher-order Markov-Gibbs Random Field (MGRF) spatial interaction model that integrates third-and fourth-order families with a traditional ...
infant brain extraction and analysis toolbox (iBEAT). respectively. ...
doi:10.1371/journal.pone.0187391
pmid:29136034
pmcid:PMC5685492
fatcat:kvx3gpreirbyliuhi74nrcky5a
aBEAT: A Toolbox for Consistent Analysis of Longitudinal Adult Brain MRI
2013
PLoS ONE
Specially, a group of image processing tools were integrated into aBEAT, including 4D brain extraction, 4D tissue segmentation, and 4D brain labeling. ...
To cater for this increasing need, we have developed a dedicated 4D Adult Brain Extraction and Analysis Toolbox (aBEAT) to provide robust and accurate analysis of the longitudinal adult brain MR images ...
A complete listing of ADNI investigators can be found at: http://adni.loni.ucla.edu/wp-content/ uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. ...
doi:10.1371/journal.pone.0060344
pmid:23577105
pmcid:PMC3616755
fatcat:yyu765tyrfhdvnvnh4hjgw7zc4
Associations of age and sex with brain volumes and asymmetry in 2–5-week-old infants
2018
Brain Structure and Function
We imaged 68 healthy infants aged 2-5 weeks with high-resolution structural MRI (magnetic resonance imaging) and investigated hemispheric asymmetry as well as the associations of various total and lobar ...
brain volumes with infant age and sex. ...
We thank our radiographer Krisse Kuvaja for performing the imaging and the FinnBrain staff as well as all the participating families. ...
doi:10.1007/s00429-018-1787-x
fatcat:qyoysaj7bzcxtiwml3ywj5ujuq
A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0–2 year age range
2015
Frontiers in Human Neuroscience
., and Shen, D. (2013). iBEAT: a toolbox for infant brain magnetic resonance image processing. ...
Magnetic resonance imaging of the newborn brain: manual segmentation of labelled atlases in term-born and preterm infants. ...
doi:10.3389/fnhum.2015.00021
pmid:25741260
pmcid:PMC4332305
fatcat:gesz4kvvqverlfobxykdeg6hkm
LABEL: Pediatric brain extraction using learning-based meta-algorithm
2012
NeuroImage
Magnetic resonance imaging of pediatric brain provides valuable information for early brain development studies. ...
In this paper, we propose a novel Learning Algorithm for Brain Extraction and Labeling (LABEL) specially for the pediatric MR brain images. ...
magnetic resonance (MR) images. ...
doi:10.1016/j.neuroimage.2012.05.042
pmid:22634859
pmcid:PMC3408835
fatcat:3knkvitpvjdundgik57hkwqrha
Processing of structural neuroimaging data in young children: Bridging the gap between current practice and state-of-the-art methods
2017
Developmental Cognitive Neuroscience
Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the ...
These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained ...
(pediatric or children or infant or neonate or newborns) and (normal or typical or healthy)/(dyslexia or autism or attention deficit hyperactivity disorder) and (MRI or magnetic resonance and T1 or T2 ...
doi:10.1016/j.dcn.2017.08.009
pmid:29033222
pmcid:PMC6969273
fatcat:nadoyjiegbajpgz23q52ihx3ry
Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts
2018
NeuroImage
The image analysis tools for neonates and young infants can be quite different from those for adults. ...
In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is ...
This work also uses the data from "Multi-visit Advanced Pediatric brain imaging study for characterizing structural and functional development (MAP Study)". ...
doi:10.1016/j.neuroimage.2018.07.004
pmid:29990581
pmcid:PMC6289773
fatcat:bxh232qww5gibgfgfy7jjbss74
Brain Deformable Registration Using Global and Local Label-Driven Deep Regression Learning in the First Year of Life
2019
IEEE Access
However, the deformable registration of infant brain magnetic resonance (MR) images is highly challenging for the following two reasons: First, there are very large anatomical and appearance variations ...
Accurate medical image registration is highly important for the quantitative analysis of infant brain dynamic development in the first year of life. ...
ACKNOWLEDGMENT We thank for the open source code of Label-reg published by Y. Hu et al. [46] . Data I were provided by Iseg Challenge and UNC. ...
doi:10.1109/access.2019.2957233
fatcat:igufnmkj6jfudgy3z24zbaf26q
Imaging the rapidly developing brain: Current challenges for MRI studies in the first five years of life
2020
Developmental Cognitive Neuroscience
One persistent challenge is that methods best suited to earlier developmental stages are suboptimal for later stages, which engenders a trade-off between using different, but age-appropriate, methods for ...
Rapid and widespread changes in brain anatomy and physiology in the first five years of life present substantial challenges for developmental structural, functional, and diffusion MRI studies. ...
We also thank Ola Ozernov-Palchik, Xi Yu, Jennifer Zuk, Jade Dunstan, Carolyn King, Kathryn Garrisi, and Joseph Sanfilippo for conceptual feedback and additional edits. ...
doi:10.1016/j.dcn.2020.100893
pmid:33341534
pmcid:PMC7750693
fatcat:3e5aoqw7nzgwlhou26raeonrga
Skull and scalp segmentation in neonatal cerebral MRI using subject-specific probability models
[article]
2022
bioRxiv
pre-print
This study presents a new approach for the segmentation of cranial bones in magnetic resonance images (MRIs) acquired from neonates in the age range of 39 to 42 weeks, gestational age. ...
Finally, a retrospective data including MRI and CT images was used which have been acquired from the same neonate within a short time interval. ...
Sona Ghadimi for her comments on the initial phase of research. ...
doi:10.1101/2022.05.06.490211
fatcat:o6vlp6g76ffkjehhjqipuhspx4
« Previous
Showing results 1 — 15 out of 18 results