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Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset [article]

Bo Li, Marius de Groot, Meike Vernooij, Arfan Ikram, Wiro Niessen, Esther Bron
2019 arXiv   pre-print
We therefore developed a novel convolutional neural network based method to directly segment white matter tract trained on a low-resolution dataset of 9149 DTI images.  ...  As a consequence, there is a large interest in the automatic segmentation of white matter tract in diffusion tensor MRI data.  ...  This is the first deep learning based method of WM tract segmentation developed on such a large-scale dataset.  ... 
arXiv:1908.10219v1 fatcat:fvjzisxtdfa5rjyfutoa7guila

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging

Bo Li, Marius de Groot, Rebecca M.E. Steketee, Rozanna Meijboom, Marion Smits, Meike W. Vernooij, M. Arfan Ikram, Jiren Liu, Wiro J. Niessen, Esther E. Bron
2020 NeuroImage  
In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.  ...  This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N=9752, 1.5T MRI).  ...  In addition, M. de Groot has a financial interest in the GSK company. The GSK had no role in this study.  ... 
doi:10.1016/j.neuroimage.2020.116993 pmid:32492510 fatcat:ropm3a5nb5ao5lf65iaagunedu

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging [article]

Bo Li, Marius de Groot, Rebecca M. E. Steketee, Rozanna Meijboom, Marion Smits, Meike W. Vernooij, M. Arfan Ikram, Jiren Liu, Wiro J. Niessen, Esther E. Bron
2020 arXiv   pre-print
In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.  ...  This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N=9752, 1.5T MRI).  ...  In addition, M. de Groot has a financial interest in the GSK company. The GSK had no role in this study.  ... 
arXiv:2005.12838v1 fatcat:k7riidy5k5e4dmczja5ld4cmwa

Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration

Bo Li, Wiro J. Niessen, Stefan Klein, Marius de Groot, M. Arfan Ikram, Meike W. Vernooij, Esther E. Bron
2021 NeuroImage  
We applied Segis-Net to the analysis of white matter tracts from N=8045 longitudinal brain MRI datasets of 3249 elderly individuals.  ...  Segis-Net approach showed a significant increase in registration accuracy, spatio-temporal segmentation consistency, and reproducibility compared with two multistage pipelines.  ...  Application to diffusion MRI The performance of Segis-Net is demonstrated by analyzing white matter tracts in a large diffusion MRI dataset, and compared to that of two multi-stage pipelines, in which  ... 
doi:10.1016/j.neuroimage.2021.118004 pmid:33794359 fatcat:q3qotochh5gy7fivri3grky3x4

Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration [article]

Bo Li, Wiro J. Niessen, Stefan Klein, Marius de Groot, M. Arfan Ikram, Meike W. Vernooij, Esther E. Bron
2020 arXiv   pre-print
We applied Segis-Net to the analysis of white matter tracts from N=8045 longitudinal brain MRI datasets of 3249 elderly individuals.  ...  Segis-Net approach showed a significant increase in registration accuracy, spatio-temporal segmentation consistency, and reproducibility comparing with two multistage pipelines.  ...  Application to diffusion MRI The performance of Segis-Net is demonstrated by analyzing white matter tracts in a large diffusion MRI dataset, and compared to that of two multi-stage pipelines, in which  ... 
arXiv:2012.14230v1 fatcat:kieonl7vnvhhfdmmamrjdb5ag4

Informative and Reliable Tract Segmentation for Preoperative Planning

Oeslle Lucena, Pedro Borges, Jorge Cardoso, Keyoumars Ashkan, Rachel Sparks, Sebastien Ourselin
2022 Frontiers in Radiology  
We use a 3D U-Net to segment white matter tracts. We then estimate model and data uncertainty using test time dropout and test time augmentation, respectively.  ...  Identifying white matter (WM) tracts to locate eloquent areas for preoperative surgical planning is a challenging task.  ...  ACKNOWLEDGMENTS We thank NVIDIA for providing the Titan V GPU used in this work.  ... 
doi:10.3389/fradi.2022.866974 fatcat:bqrh3oxsnrbhheja325hdhxpny

A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes [article]

Bo Li, Wiro Niessen, Stefan Klein, Marius de Groot, Arfan Ikram, Meike Vernooij, Esther Bron
2019 arXiv   pre-print
We applied this method to the segmentation of white matter tracts, describing functionally grouped axonal fibers, using N=8045 longitudinal brain MRI data of 3249 individuals.  ...  Registration between time-points is used either as a prior for segmentation in a subsequent time point or to perform segmentation in a common space.  ...  The framework was evaluated on longitudinal white matter tracts analysis using a large-scale diffusion MRI dataset.  ... 
arXiv:1908.10221v1 fatcat:vphuywjrhndflj7vopd7szsl74

Methods and considerations for longitudinal structural brain imaging analysis across development

Kathryn L. Mills, Christian K. Tamnes
2014 Developmental Cognitive Neuroscience  
We focus on measurements of brain morphometry (e.g., volume, cortical thickness, surface area, folding patterns), as well as measurements derived from diffusion tensor imaging (DTI).  ...  Results from these studies have given us a glimpse into the remarkably extended and multifaceted development of our brain, converging with evidence from anatomical and histological studies.  ...  Anne-Lise Goddings for providing the initial inspiration for this review, as well as for many helpful conversations on the topic.  ... 
doi:10.1016/j.dcn.2014.04.004 pmid:24879112 pmcid:PMC6989768 fatcat:bz4k6rrmlfacbbgiqfutax6zwi

Mean apparent propagator (MAP) MRI: A novel diffusion imaging method for mapping tissue microstructure

Evren Özarslan, Cheng Guan Koay, Timothy M. Shepherd, Michal E. Komlosh, M. Okan İrfanoğlu, Carlo Pierpaoli, Peter J. Basser
2013 NeuroImage  
The lowest order term in this expansion contains a diffusion tensor that characterizes the Gaussian displacement distribution, equivalent to diffusion tensor MRI (DTI).  ...  We also define and map novel quantitative descriptors of diffusion that can be computed robustly using this MAP-MRI framework.  ...  A diffusion-weighted multislice spin echo EPI pulse sequence with 4 segments was used.  ... 
doi:10.1016/j.neuroimage.2013.04.016 pmid:23587694 pmcid:PMC4059870 fatcat:ihzvrgdp7nf5lillgo4occbrra

A framework for spatial normalization and voxelwise analysis of diffusion propagators in multiple MAP-MRI data sets [article]

Alexandru V Avram, Adam S Bernstein, M. Okan Irfanoglu, Craig C. Weinkauf, Martin Cota, Neville Gai, Amber Simmons, Anita Moses, L. Christine Turtzo, Neekita Jikaria, Lawrence Latour, Dzung Pham (+2 others)
2019 bioRxiv   pre-print
First, we compute a DTI study template which provides the reference frame and scaling parameters needed to construct a standardized set of MAP-MRI basis functions at each voxel in template space.  ...  We illustrate the application of this method by generating a template of MAP propagators for a cohort of healthy volunteers and show a proof-of-principle example of how this pipeline may be used to detect  ...  We identified white matter structures based on the International Consortium of Brain Mapping (ICBM)-DTI-81 atlas.  ... 
doi:10.1101/697284 fatcat:tpczdf43qbgcddf6txr7om4mty

From Diffusion MRI to Brain Connectomics [chapter]

Aurobrata Ghosh, Rachid Deriche
2012 Modeling in Computational Biology and Biomedicine  
We reproduce here only the final example. 675 Using the affine invariant Riemannian metric on Sym + 3 , which also forms a Riemannian metric on 676 the space of 3D Gaussian distributions N (x, r), it is  ...  segmentation framework using this metric for DTI.  ... 
doi:10.1007/978-3-642-31208-3_6 fatcat:yie47qd3ezc4jivnqpyfo62rju

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

Ilaria Boscolo Galazzo, Lorenza Brusini, Silvia Obertino, Mauro Zucchelli, Cristina Granziera, Gloria Menegaz
2018 Frontiers in Neuroscience  
Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity.  ...  Reproducibility of all the indices on both WM and GM was quantitatively proved on controls.  ...  In particular, both 3D-SHORE-based and DTI indices exhibited high reproducibility, as quantified by ICC, and high stability, as quantified by intra/inter-subject CV parameters, on both tract and region-based  ... 
doi:10.3389/fnins.2018.00092 pmid:29515362 pmcid:PMC5826355 fatcat:6dlax2nflffuhj5emk534ym6s4

Diffusion-Weighted Imaging of the Spinal Cord [chapter]

Benjamin M. Ellingson, Julien Cohen-Adad
2014 Quantitative MRI of the Spinal Cord  
TRACTOGRAPHY Fiber tracking or tractography uses information from DWI data to obtain a 3D representation of fiber architecture in the white matter.  ...  assess specific white matter tracts.  ... 
doi:10.1016/b978-0-12-396973-6.00009-5 fatcat:2pzz7ydv2rcvhmn7zuhsows7si

Tracking white-matter brain modifications in chronic non-bothersome acoustic trauma tinnitus

Chloé Jaroszynski, Arnaud Attyé, Agnès Job, Chantal Delon-Martin
2021 NeuroImage: Clinical  
We conducted a deep-learning based tractography segmentation and mapped Apparent Fiber Density (AFD) on the bundles of interest.  ...  To date, the specific role of white matter abnormalities related to tinnitus reaches no consensus in the literature.  ...  This study was performed on the IRMaGe platform member of France Life Imaging network (Grant ANR-11-INBS-0006).  ... 
doi:10.1016/j.nicl.2021.102696 pmid:34029920 fatcat:sm2is3djf5f6pfldhrpu4seq4y

Enhancing the Estimation of Fiber Orientation Distributions using Convolutional Neural Networks

Oeslle Lucena, Sjoerd B. Vos, Vejay Vakharia, John Duncan, Keyoumars Ashkan, Rachel Sparks, Sebastien Ourselin
2021 Computers in Biology and Medicine  
We evaluate U-Net and High-Resolution Network (HighResNet) 3D CNN architectures on data from the Human Connectome Project and an in-house dataset.  ...  than used to train the CNN; and 3) when testing on a dataset with a fewer number of gradient directions than used to train the CNN.  ...  We evaluate U-Net and High-Resolution Network (HighResNet) 3D CNN architectures on data from the Human Connectome Project and an in-house dataset.  ... 
doi:10.1016/j.compbiomed.2021.104643 pmid:34280774 fatcat:76tw73wenfcarfov4se3apklbe
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