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A pediatric brain structure atlas from T1-weighted MR images

Zuyao Y. Shan, Carlos Parra, Qing Ji, Robert J. Ogg, Yong Zhang, Fred H. Laningham, Wilburn E. Reddick, Kevin R. Cleary, Robert L. Galloway, Jr.
2006 Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display  
Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl.  ...  In this paper, we have developed a digital atlas of the pediatric human brain.  ...  Zuyao Shan and the Cancer Center Support Grant (CA21765) from the National Cancer Institute and by the American Lebanese Syrian Associated Charities (ALSAC).  ... 
doi:10.1117/12.651922 dblp:conf/miigp/ShanPJOZLR06 fatcat:zuph7pftava2ji7zlvdq52vcw4

A Digital Pediatric Brain Structure Atlas from T1-Weighted MR Images [chapter]

Zuyao Y. Shan, Carlos Parra, Qing Ji, Robert J. Ogg, Yong Zhang, Fred H. Laningham, Wilburn E. Reddick
2006 Lecture Notes in Computer Science  
Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1-weighted MR data set of a 9-year old, right-handed girl.  ...  Human brain atlases are indispensable tools in model-based segmentation and quantitative analysis of brain structures.  ...  Zuyao Shan and the Cancer Center Support Grant (CA21765) from the National Cancer Institute and by the American Lebanese Syrian Associated Charities (ALSAC).  ... 
doi:10.1007/11866763_41 fatcat:tihhedyqcjdj7alew7nyao46sa

Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles

Xiaoying Tang, Deana Crocetti, Kwame Kutten, Can Ceritoglu, Marilyn S. Albert, Susumu Mori, Stewart H. Mostofsky, Michael I. Miller
2015 Frontiers in Neuroscience  
We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain.  ...  There are two stages in the proposed pipeline; first the input T1-weighted image is automatically skull-stripped via a fast MALF, then internal brain structures of interest are automatically extracted  ...  Ament, Timothy Brown, Huong Trinh, Haiyan Chi, and Neil Kelly for their efforts in manually skullstripping and delineating various brain structures for the validation analysis.  ... 
doi:10.3389/fnins.2015.00061 pmid:25784852 pmcid:PMC4347448 fatcat:bnbxwacagvejjgph6hi6pns25q

Pediatric Patients Demonstrate Progressive T1-Weighted Hyperintensity in the Dentate Nucleus following Multiple Doses of Gadolinium-Based Contrast Agent

D.R. Roberts, A.R. Chatterjee, M. Yazdani, B. Marebwa, T. Brown, H. Collins, G. Bolles, J.M. Jenrette, P.J. Nietert, X. Zhu
2016 American Journal of Neuroradiology  
We investigated the relationship between the number of prior gadolinium-based contrast agent doses and increasing T1 signal in the dentate nucleus on unenhanced T1-weighted MR imaging.  ...  , the pediatric brain would also demonstrate dose-dependent increasing T1 signal in the dentate nucleus.  ...  (R) (MR), and Sarah L. Brewer in preparing the data for this article.  ... 
doi:10.3174/ajnr.a4891 pmid:27469211 pmcid:PMC5161565 fatcat:fitxiojax5cf3opormhfahh5x4

A Tool to Investigate Symmetry Properties of Newborns Brain: The Newborns' Symmetric Brain Atlas

Negar Noorizadeh, Kamran Kazemi, Reinhard Grebe, Mohammad Sadegh Helfroush, Mahdi Mahmoudzadeh, Fabrice Wallois
2013 ISRN Neuroscience  
Thus, in this paper we present our framework to create a symmetric brain atlas from a group of newborns aged between 39 and 42 weeks after gestation.  ...  Until now most atlases used for image processing contain themselves asymmetry and may thus introduce and/or increase asymmetry already contained in the original data of brain structural or functional images  ...  Hence, this paper presents a method to create a symmetric neonate brain atlas using T1-weighted MR images from subjects in their first month of life.  ... 
doi:10.1155/2013/317215 pmid:24967308 pmcid:PMC4045561 fatcat:ti76ywejxjgnnirgttlsahvfvm

Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi-platform and multi-institution clinical images

Yangming Ou, Randy L. Gollub, Kallirroi Retzepi, Nathaniel Reynolds, Rudolph Pienaar, Steve Pieper, Shawn N. Murphy, P. Ellen Grant, Lilla Zöllei
2015 NeuroImage  
Currently, most existing brain extraction methods are optimized for structural T1-weighted MR images of fully myelinated brains.  ...  This paper presents a multi-atlas framework for the brain extraction of pediatric ADC maps.  ...  Acknowledgments The authors would like to thank Katie Murphy for her extensive and careful reviewing of the radiological reports and patient records, which guaranteed that the pediatric subjects in the  ... 
doi:10.1016/j.neuroimage.2015.08.002 pmid:26260429 pmcid:PMC4966541 fatcat:gvgcrn4adbd6ndzdrazuy3xz5u

Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging"

Kenichi Oishi, Andreia V. Faria, Shoko Yoshida, Linda Chang, Susumu Mori
2014 International Journal of Developmental Neuroscience  
In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population.  ...  To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required  ...  ), and from the National Center for Research Resources grant G12-RR003061.  ... 
doi:10.1016/j.ijdevneu.2013.11.006 pmid:24295553 pmcid:PMC4696018 fatcat:yrepor4r3banxiah4yw5zr2t2y

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging

Kenichi Oishi, Andreia V. Faria, Shoko Yoshida, Linda Chang, Susumu Mori
2013 International Journal of Developmental Neuroscience  
In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population.  ...  To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required  ...  ), and from the National Center for Research Resources grant G12-RR003061.  ... 
doi:10.1016/j.ijdevneu.2013.06.004 pmid:23796902 pmcid:PMC3830705 fatcat:caaosevedrfslnrv3yvpqxqt5a

Human Brain Myelination from Birth to 4.5 Years [chapter]

Berengere Aubert-Broche, Vladimir Fonov, Ilana Leppert, G. Bruce Pike, D. Louis Collins
2008 Lecture Notes in Computer Science  
The original contribution of this study is to develop a method to characterize and visualize the myelination pattern using MRI data from a group of normal subjects from birth to just over 4 years of age  ...  Even if the myelination is a continuous process, it is useful to characterize myelination evolution in normal brain development in order to better study demyelinating diseases.  ...  [5] classified MR images from 1 and 2 year old children using a probabilistic atlas specifically for 1 and 2 year olds. Gildmore et al.  ... 
doi:10.1007/978-3-540-85990-1_22 fatcat:pjsfpvn32nf4vbufcz3wgcqzcm

Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression

Ahmed Serag, Paul Aljabar, Gareth Ball, Serena J. Counsell, James P. Boardman, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Daniel Rueckert
2012 NeuroImage  
In this paper we present an approach for constructing a 4D atlas of the developing brain, between 28 and 44 weeks post-menstrual age at time of scan, using T1 and T2 weighted MR images from 204 premature  ...  A better understanding of brain development requires a spatiotemporal atlas that characterizes the dynamic changes during this period.  ...  Acknowledgments We are grateful for support from the 'Chloe-Svider' grant. We thank the families who took part in the study.  ... 
doi:10.1016/j.neuroimage.2011.09.062 pmid:21985910 fatcat:ka37g7j2aba6riqjls523ugczi

Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning [article]

Camilo Bermudez, Justin Blaber, Samuel W. Remedios, Jess E. Reynolds, Catherine Lebel, Maureen McHugo, Stephan Heckers, Yuankai Huo, Bennett A. Landman
2019 arXiv   pre-print
Recently, the Spatially Localized Atlas Network Tiles (SLANT) approach has been shown to effectively segment whole brain non-contrast T1w MRI with 132 volumetric labels.  ...  Generalizability is an important problem in deep neural networks, especially in the context of the variability of data acquisition in clinical magnetic resonance imaging (MRI).  ...  The imaging dataset(s) used for the analysis described were obtained from ImageVU, a research repository of medical imaging data and image-related metadata.  ... 
arXiv:1908.04702v1 fatcat:sanwhoc4tneznm5tcxjzpp7i6a

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping

Yuyao Zhang, Hongjiang Wei, Matthew J. Cronin, Naying He, Fuhua Yan, Chunlei Liu
2018 NeuroImage  
Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2weighted MRI.  ...  Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map.  ...  (b) T1-weighted and QSM atlases guided by QSM only. (c) T1-weighted and QSM atlases guided by T1-weighted images only.  ... 
doi:10.1016/j.neuroimage.2018.01.008 pmid:29325780 pmcid:PMC5857468 fatcat:cqrpqey6dza3rcyrt67ubx5cpe

Cortical enhanced tissue segmentation of neonatal brain MR images acquired by a dedicated phased array coil

Feng Shi, Pew-Thian Yap, Yong Fan, Jie-Zhi Cheng, L.L. Wald, G. Gerig, Weili Lin, Dinggang Shen
2009 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images.  ...  To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition  ...  Because we aim to extract brighter structures from a darker background in the T1-weighted image ( Fig. 5 ; note that the intensity is inverse in the T2-weighted image), λ 2 and λ 3 should be negative  ... 
doi:10.1109/cvpr.2009.5204348 pmid:20862268 pmcid:PMC2941911 fatcat:zepnfmalqjfvzlb3vkxwoowfhy

Novel solutions toward high accuracy automatic brain tissue classification in young children [article]

Nataliya Portman, Paule-J Toussaint, Alan C. Evans McConnell
2020 arXiv   pre-print
A poor and highly variable grey matter and white matter contrast on T1-weighted MR scans of developing brains complicates the automatic categorization of voxels into major tissue classes using state-of-the-art  ...  Accurate automatic classification of major tissue classes and the cerebrospinal fluid in pediatric MR scans of early childhood brains remains a challenge.  ...  This project was funded in whole or in part by the Montreal Neurological Institute in the form of a postdoctoral fellowship, the National Institute of Child Health and Human Development, the National Institute  ... 
arXiv:2005.03261v1 fatcat:ynygsgho45hu7mlszfetduooqi

Deep Learning-Based Studies on Pediatric Brain Tumors Imaging: Narrative Review of Techniques and Challenges

Hala Shaari, Jasmin Kevrić, Samed Jukić, Larisa Bešić, Dejan Jokić, Nuredin Ahmed, Vladimir Rajs
2021 Brain Sciences  
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.  ...  Brain tumors diagnosis in children is a scientific concern due to rapid anatomical, metabolic, and functional changes arising in the brain and non-specific or conflicting imaging results.  ...  A FCN was developed in 2016 in the form of segmentation of isointense phase brain MR images [57] . They operate a convolution-pooling stream for multi-modality data from T1, T2 and FA images.  ... 
doi:10.3390/brainsci11060716 pmid:34071202 fatcat:usmduuhzyzcsrh7lgto3ejzbfu
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