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Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training

Ilwoo Lyu, Shuxing Bao, Lingyan Hao, Jewelia Yao, Jacob A Miller, Willa Voorhies, Warren D Taylor, Silvia A Bunge, Kevin S Weiner, Bennett A Landman
2021 NeuroImage  
In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional  ...  We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation.  ...  This is a general issue in modern deep neural networks regardless of data augmentation.  ... 
doi:10.1016/j.neuroimage.2021.117758 pmid:33497773 pmcid:PMC8366030 fatcat:bwsbaooksvecbpqhkidgvrdtma

A new tripartite landmark in posterior cingulate cortex [article]

Ethan H. Willbrand, Benjamin J. Parker, Willa I. Voorhies, Jacob A. Miller, Ilwoo Lyu, Tyler Hallock, Lyndsey Aponik-Gremillion, Silvia Bunge, Brett L. Foster, Kevin S. Weiner
2021 bioRxiv   pre-print
Manually labeling 4,319 sulci in 552 hemispheres, we discovered a consistently localized shallow cortical indentation (termed the inframarginal sulcus; ifrms) within PCC that is absent from neuroanatomical  ...  These findings support a classic theory that shallow, tertiary sulci serve as landmarks in association cortices. They also beg the question: how many other cortical indentations have we missed?  ...  We used recently developed (Methods 37 ) spherical convolutional neural networks (CNNs) with context-aware training on the eight PMC sulci identified in the young adult participants.  ... 
doi:10.1101/2021.10.30.466521 fatcat:iq3oq2td7rhuxnxoin6d5pkm3u

Quantitative in vivo MRI measurement of cortical development in the fetus

Cédric Clouchoux, Dimitri Kudelski, Ali Gholipour, Simon K. Warfield, Sophie Viseur, Marine Bouyssi-Kobar, Jean-Luc Mari, Alan C. Evans, Adre J. du Plessis, Catherine Limperopoulos
2011 Brain Structure and Function  
We describe the in vivo fetal gyrification process using a robust feature extraction algorithm applied directly on the cortical surface, providing an explicit delineation of the sulcal pattern during fetal  ...  In this study, we investigate the in vivo fetal cortical folding pattern in healthy fetuses between 25 and 35 weeks gestational age using 3-D reconstructed fetal cortical surfaces.  ...  We are indebted to the families for participating in this study.  ... 
doi:10.1007/s00429-011-0325-x pmid:21562906 fatcat:dmi4xxvhrvdgllzktwv5mfp2ra

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 Sensors  
As such, graph neural networks have attracted significant attention by exploiting implicit information that resides in a biological system, with interacting nodes connected by edges whose weights can be  ...  We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21144758 fatcat:jytyt4u2pjgvhnhcto3vcvd3a4

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future [article]

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 arXiv   pre-print
As such, graph neural networks have attracted significant attention by exploiting implicit information that resides in a biological system, with interactive nodes connected by edges whose weights can be  ...  We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure and electrical-based analysis.  ...  The same authors also implement a spherical U-Net for cortical sulci labeling from relatively few samples in a developmental cohort [27] .  ... 
arXiv:2105.13137v1 fatcat:gm7d2ziagba7bj3g34u4t3k43y

The need for improved brain lesion segmentation techniques for children with cerebral palsy: A review

Alex M. Pagnozzi, Yaniv Gal, Roslyn N. Boyd, Simona Fiori, Jurgen Fripp, Stephen Rose, Nicholas Dowson
2015 International Journal of Developmental Neuroscience  
In this paper, we present a review of a subset of available brain injury segmentation approaches that could be applied to CP, including the detection of cortical malformations, white and grey matter lesions  ...  The need for improved brain lesion segmentation techniques for children with cerebral palsy: a review.International Journal of Developmental Neuroscience http://dx.  ...  Roslyn Boyd is supported by a NHMRC Career Development Fellowship (1037220) and a NHMRC Project Grant COMBIT (1003887). No other authors have potential conflicts of interest to declare.  ... 
doi:10.1016/j.ijdevneu.2015.08.004 pmid:26394278 fatcat:bphc4r2blbenhecjydluue3j5a

Mapping fetal brain development based on automated segmentation and 4D brain atlasing [article]

Haotian Li, Guohui Yan, Wanrong Luo, Tintin Liu, Yan Wang, Ruibin Liu, Weihao Zheng, Yi Zhang, Kui Li, Li Zhao, Catherine Limperopoulos, Yu Zou (+1 others)
2020 bioRxiv   pre-print
First, we designed a U-net convolutional neural network for automated fetal brain extraction, which achieved an average accuracy of 97%.  ...  gestation in a Chinese population.  ...  Kleesiek et al. used a convolutional neural network (CNN) for adult brain extraction, with used cubic windows of a fixed size around each voxel (Kleesiek et al., 2016) .  ... 
doi:10.1101/2020.05.10.085381 fatcat:iqu6dayh3bgwbmuci7q4lpuhwe

Age-specific Structural Fetal Brain Atlases Construction and Cortical Development Quantification for Chinese Population

Jiangjie Wu, Taotao Sun, Boliang Yu, Zhenghao Li, Qing Wu, Yutong Wang, Zhaoxia Qian, Yuyao Zhang, Ling Jiang, Hongjiang Wei
2021 NeuroImage  
In this paper, we use an unbiased template construction algorithm to create a set of age-specific Chinese fetal atlases between 21-35 weeks of gestation from 115 normal fetal brains.  ...  Additionally, a direct comparison of the Chinese fetal atlases and Caucasian fetal atlases reveals dramatic anatomical differences, mainly in the medial frontal and temporal regions.  ...  Briefly, a Convolutional Neural Network (CNN) was firstly used to automatically localize the fetal brain in each input LR stack to obtain an initial segmentation of the fetal brain.  ... 
doi:10.1016/j.neuroimage.2021.118412 pmid:34298085 fatcat:qntt24vjq5gztgncw6vckbw6yq

Neuroimage signature from salient keypoints is highly specific to individuals and shared by close relatives

Laurent Chauvin, Kuldeep Kumar, Christian Wachinger, Marc Vangel, Jacques de Guise, Christian Desrosiers, William Wells, Matthew Toews
2019 NeuroImage  
Here, we propose to model individual variability using a distinctive keypoint signature: a set of unique, localized patterns, detected automatically in each image by a generic saliency operator.  ...  Neuroimaging studies typically adopt a common feature space for all data, which may obscure aspects of neuroanatomy only observable in subsets of a population, e.g. cortical folding patterns unique to  ...  Keypoint detection here is based on a recursive Gaussian filtering process that is analogous to a highly efficient, unbiased convolutional neural network (CNN) used in deep learning (LeCun et al., 2015  ... 
doi:10.1016/j.neuroimage.2019.116208 pmid:31546048 pmcid:PMC6931906 fatcat:yalnyvwlbrettgz37hnd54jg3q

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review [article]

Fan Zhang, Alessandro Daducci, Yong He, Simona Schiavi, Caio Seguin, Robert Smith, Chun-Hung Yeh, Tengda Zhao, Lauren J. O'Donnell
2021 arXiv   pre-print
In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease.  ...  Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape.  ...  CHY is grateful to the Ministry of Science and Technology of Taiwan (MOST 109-2222-E-182-001-MY3) for the support.  ... 
arXiv:2104.11644v1 fatcat:l3ixpcwu7jb7zcqo2sm5pswmja

The NonHuman Primate Neuroimaging & Neuroanatomy Project

Takuya Hayashi, Yujie Hou, Matthew F Glasser, Joonas A Autio, Kenneth Knoblauch, Miho Inoue-Murayama, Tim Coalson, Essa Yacoub, Stephen Smith, Henry Kennedy, David C Van Essen
2021 NeuroImage  
We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth  ...  Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans.  ...  Acknowledgements This study is supported by a grant Brain/MINDS -beyond from References under revision of this special issue of NeuroImage Autio, J.A., Zhu, Q., Li, X., Glasser, M.F., Schwiedrzik,  ... 
doi:10.1016/j.neuroimage.2021.117726 pmid:33484849 pmcid:PMC8079967 fatcat:tfv3sm6xpjfnfj2uarpqwnyc5u

The NonHuman Primate Neuroimaging Neuroanatomy Project [article]

Takuya Hayashi, Yujie Hou, Matthew F Glasser, Joonas A Autio, Kenneth Knoblauch, Miho Inoue-Murayama, Tim Coalson, Essa Yacoub, Stephen Smith, Henry Kennedy, David C Van Essen
2021 arXiv   pre-print
We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth  ...  However, ground truth validation of connectivity using invasive tracers is not feasible in humans.  ...  A standardized venous map is used for creating a subject-specific venous map, which is then used for extracting the time series as a feature when automatically denoising functional MRI data using ICA+FIX  ... 
arXiv:2010.00308v3 fatcat:xqccnaz2hzcs7pqedcutkvktea

A collaborative resource platform for non-human primate neuroimaging [article]

Adam Messinger, Nikoloz Sirmpilatze, Katja Heuer, Kep Kee Loh, Rogier Mars, Julien Sein, Ting Xu, Daniel Glen, Benjamin Jung, Jakob Seidlitz, Paul Taylor, Roberto Toro (+20 others)
2020 biorxiv/medrxiv   pre-print
Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions.  ...  Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience.  ...  A convolutional neural network model for skull-stripping of NHP images.  ... 
doi:10.1101/2020.07.31.230185 fatcat:6vpogby2ezhu3jgxnpjlkbt3ai

Modeling & Analysis

2003 NeuroImage  
For each brain, the main cortical sulci are automatically extracted and recognized using a set of processing tools freely available on "http://anatomist.info" [5].  ...  Abstract A new neural network algorithm has been developed for the automatic visual segmentation of T1-weighted 3-D head magnetic resonance images.  ...  This paradigm has been extensively used in electrophysiological recordings of single cell activity in various cortical areas of non-human primates in order to characterize the relation between grip force  ... 
doi:10.1016/s1053-8119(05)70006-9 fatcat:zff2suxcofbxvetfrwfwcxi3zm

Connectivity-Driven Parcellation Methods for the Human Cerebral Cortex [article]

Salim Arslan
2018 arXiv   pre-print
Second, we cast the parcellation problem as a feature reduction problem and make use of manifold learning and image segmentation techniques to identify cortical regions with distinct structural connectivity  ...  Our contributions are four-fold: First, we propose a clustering approach to delineate a cortical parcellation that provides a reliable abstraction of the brain's functional organisation.  ...  Acknowledgements I would like to first of all thank my supervisor Daniel Rueckert for giving me the opportunity  ... 
arXiv:1802.06772v1 fatcat:zeu6okppcnbhjakwyoe3gf64pi
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