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Tools for multiple granularity analysis of brain MRI data for individualized image analysis
2014
NeuroImage
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Voxel-based analysis is widely used for quantitative analysis of brain MRI. ...
The multiple atlases were then applied to T1-weighted MR images of each subject data for automated brain parcellation and five levels of ontological relationships were established, which further reduced ...
structural relationships -Our approach examines the brain anatomy from multiple granularity levels -Our approach is suitable for phenotype analysis of individual patients Comparison of granularity reduction ...
doi:10.1016/j.neuroimage.2014.06.046
pmid:24981408
pmcid:PMC4165692
fatcat:tvri4jfx7nhjtjocfiqcb7hbpa
Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool
2015
PLoS ONE
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When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. ...
The entire brain was parceled into five different levels of granularity. ...
Conclusion We describe the use of a fully automated image parcellation tool for brain MRI, using a multiatlas approach. ...
doi:10.1371/journal.pone.0133533
pmid:26208327
pmcid:PMC4514626
fatcat:3esmuc5pt5dc3catxheo6sg22q
Content-based image retrieval for brain MRI: An image-searching engine and population-based analysis to utilize past clinical data for future diagnosis
2015
NeuroImage: Clinical
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Brain MRI Content-based image retrieval Atlas-based analysis Radiological diagnosis is based on subjective judgment by radiologists. ...
We explored and tested the power of individual classifications and of performing a search for images with similar anatomical features in a database using partial least squares-discriminant analysis (PLS-DA ...
We thank NIH (grants P41RR15241, RO1AG20012, and RO1NS058299 (SM), RO1HD065955 (KO), RO3EB014357 (AVF), R01 DC011317 and R01 DC 03681 (AH)) for financial support. ...
doi:10.1016/j.nicl.2015.01.008
pmid:25685706
pmcid:PMC4309952
fatcat:hhel3q5e6rdb7mcoxb5uehqfyy
Atlas-Based Neuroinformatics via MRI: Harnessing Information from Past Clinical Cases and Quantitative Image Analysis for Patient Care
2013
Annual Review of Biomedical Engineering
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Despite the rapid progress of image analysis technologies for magnetic resonance imaging of the human brain, these methods have not been widely adopted for clinical diagnoses. ...
As these are indexed via parametric representations, we can use image retrieval tools to search for phenotypes along with their clinical metadata. ...
The content of this Article is solely the responsibility of the authors and do not necessarily represent the official view of any of the institutes.
LITERATURE CITED ...
doi:10.1146/annurev-bioeng-071812-152335
pmid:23642246
pmcid:PMC3719383
fatcat:t24iyi4rybalhm4y77sxapzpsi
Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
2022
Cancers
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Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. ...
Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis ...
At present, magnetic resonance imaging (MRI) is a key tool for the diagnosis and treatment monitoring of brain tumors. ...
doi:10.3390/cancers14030464
pmid:35158732
pmcid:PMC8833690
fatcat:ly35atvdzvf7jft2dgzighnfti
Brain MRI Pattern Recognition Translated to Clinical Scenarios
2017
Frontiers in Neuroscience
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The independent variables were the volumes of 283 anatomical areas, derived from automated segmentation of T1-high resolution brain MRIs. ...
The segmentation based volumetric quantification reduces image dimensionality from the voxel level [on the order of O(10 6 )] to anatomical structures [O(10 2 )] for subsequent statistical analysis. ...
ACKNOWLEDGMENTS We are grateful to the individuals who participated in this research. We thank Dr. Argye Hillis, Dr. Christopher Ross, and Dr. Sarah Ying, for data sharing. ...
doi:10.3389/fnins.2017.00578
pmid:29104527
pmcid:PMC5655969
fatcat:chqh4q3x7vfbxbh6wi2yhbcc6a
Cloud-Based Brain Magnetic Resonance Image Segmentation and Parcellation System for Individualized Prediction of Cognitive Worsening
2019
Journal of Healthcare Engineering
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Despite multiple efforts to apply computational brain magnetic resonance image (MRI) analysis in predicting cognitive worsening, with several successes, brain MRI is not routinely quantified in clinical ...
Each MRI was parcellated into 265 anatomical units based on the MRICloud fully automated image segmentation function, to measure the volume of each parcel. ...
Data collection and sharing for this project was funded by the Alzheimer's ...
doi:10.1155/2019/9507193
pmid:30838124
pmcid:PMC6374863
fatcat:jdjoc2mq4bgnvnahvdthbwro7i
Investigating microstructural variation in the human hippocampus using non-negative matrix factorization
2019
NeuroImage
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Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component ...
Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. ...
Ragini Verma (Professor in Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania) for her discussion and consultations regarding diffusion processing. ...
doi:10.1016/j.neuroimage.2019.116348
pmid:31715254
fatcat:g6o2ydjg5nc5rp26izpxjhggxu
A Framework for Cortical Layer Composition Analysis using Low Resolution T1 MRI Images
[article]
2018
bioRxiv
pre-print
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We use a low resolution echo planar imaging inversion recovery (EPI IR) MRI scan protocol that provides fast acquisition (~12 minutes) and enables extraction of multiple T1 relaxation time components per ...
Despite technological advancements in the field of high resolution MRI, accurate estimation of whole brain layer composition has remained limited due to partial volume effects, leaving some layers far ...
IR Decay Function Fit These data were used for multiple T1 analysis, by calculating T1 values and their corresponding partial volumes on a voxel-by-voxel basis. ...
doi:10.1101/390112
fatcat:733efbdwqvdkjd5dejgnv3axxa
Modelling cortical laminar connectivity in the macaque brain
[article]
2020
bioRxiv
pre-print
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We use multi-modal ex-vivo MRI imaging of both white and grey matter, which are then integrated via our simple model of laminar connectivity. ...
In this work, we revisit laminar-level connectivity in the macaque brain using a whole-brain MRI-based approach. ...
IR decay function fit: The IR 3D FLASH data were used for multiple T1 analysis, by calculating T1 values and their corresponding partial volumes on a voxel-by-voxel basis. ...
doi:10.1101/2020.07.19.210526
fatcat:nuy7kolaqba6revo6zdhbjcmca
MR Diffusion Histology and Micro-Tractography Reveal Mesoscale Features of the Human Cerebellum
2013
Cerebellum
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State-of-the-art in vivo magnetic resonance imaging (MRI) methods, such as diffusion tractography techniques, can reveal trajectories of the major white matter pathways, but their correspondence with underlying ...
Current histological techniques provide powerful methods for unravelling local axonal architecture, but the relatively low volume of data that can be acquired in a reasonable amount of time limits their ...
Po-Wah So, the manager of the preclinical imaging unit at KCL, and the British Heart Foundation for funding the 7T MRI scanner. ...
doi:10.1007/s12311-013-0503-x
pmid:23907655
pmcid:PMC3824945
fatcat:fxexf6gfvng6vkbcyqwjl74ib4
A collaborative resource platform for non-human primate neuroimaging
[article]
2020
biorxiv/medrxiv
pre-print
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PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. ...
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. ...
Acknowledgements We would like to thank Patrick Markwalter for assistance with compiling references, editing and formatting. ...
doi:10.1101/2020.07.31.230185
fatcat:6vpogby2ezhu3jgxnpjlkbt3ai
A collaborative resource platform for non-human primate neuroimaging
2021
NeuroImage
Preserved Fulltext
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The file type is application/pdf.
PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. ...
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. ...
Acknowledgements We would like to thank Patrick Markwalter for assistance with compiling references, editing and formatting. ...
doi:10.1016/j.neuroimage.2020.117519
pmid:33227425
fatcat:67ng3nt3uvbg3l4n4prlshuuwi
Imaging whole-brain cytoarchitecture of mouse with MRI-based quantitative susceptibility mapping
2016
NeuroImage
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The proper microstructural arrangement of complex neural structures is essential for establishing the functional circuitry of the brain. ...
We present an MRI method to resolve tissue microstructure and infer brain cytoarchitecture by mapping the magnetic susceptibility in the brain at high resolution. ...
R21HL122759, and by the National Multiple Sclerosis Society through grant RG4723. ...
doi:10.1016/j.neuroimage.2016.05.033
pmid:27181764
pmcid:PMC5201162
fatcat:24mkcl2sfrhpbpc7ije3jvqhwi
Construction and application of human neonatal DTI atlases
2015
Frontiers in Neuroanatomy
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Moreover, ABA can be used in high-throughput analysis to efficiently process medical images and to assess longitudinal brain changes. ...
Future directions for this method include research designed to increase the accuracy of the image parcellation. ...
subject brain atlas
of the neonatal brain that integrates DTI-data
with co-registered anatomical MRI. ...
doi:10.3389/fnana.2015.00138
pmid:26578899
pmcid:PMC4620146
fatcat:h3kibxisgfbunpnn2jnfawb6ci
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