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MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Adriënne M. Mendrik, Koen L. Vincken, Hugo J. Kuijf, Marcel Breeuwer, Willem H. Bouvy, Jeroen de Bresser, Amir Alansary, Marleen de Bruijne, Aaron Carass, Ayman El-Baz, Amod Jog, Ranveer Katyal (+18 others)
2015 Computational Intelligence and Neuroscience  
We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain  ...  Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others.  ...  of study participants and MRI acquisition at the UMC Utrecht  ... 
doi:10.1155/2015/813696 pmid:26759553 pmcid:PMC4680055 fatcat:uhsmxrfz65ahtc7fciqt6v3fem

Simulation and Validation in Brain Image Analysis

Jussi Tohka, Pierre Bellec, Christophe Grova, Anthonin Reilhac
2016 Computational Intelligence and Neuroscience  
Acknowledgments We thank all the authors for submitting their papers to this special issue as well as the reviewers for providing their expertise and time to evaluate and improve the papers.  ...  In "MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans" A. M.  ...  Mendrik et al. describe an online platform to evaluate tissue segmentation in structural brain magnetic resonance imaging (MRI).  ... 
doi:10.1155/2016/1041058 pmid:27433159 pmcid:PMC4940532 fatcat:4pgunkb3ona2hiosa4uult46yi

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson
2017 Journal of digital imaging  
This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI.  ...  Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest.  ...  MRBrainS The aim of the MRBrainS evaluation framework is to compare algorithms for segmentation of gray matter, white matter, and cerebrospinal fluid on multi-sequence (T1weighted, T1-weighted-inversion  ... 
doi:10.1007/s10278-017-9983-4 pmid:28577131 pmcid:PMC5537095 fatcat:lekbdtmkx5cchmuutntacymrzu

Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets [article]

Reuben Dorent, Thomas Booth, Wenqi Li, Carole H. Sudre, Sina Kafiabadi, Jorge Cardoso, Sebastien Ourselin, Tom Vercauteren
2020 arXiv   pre-print
Brain tissue segmentation from multimodal MRI is a key building block of many neuroimaging analysis pipelines.  ...  However, few existing approaches allow for the joint segmentation of normal tissue and brain lesions.  ...  As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.  ... 
arXiv:2009.04009v1 fatcat:42c67fdsgvgh5n77upgqxrqlhu

Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets

Reuben Dorent, Thomas Booth, Wenqi Li, Carole H. Sudre, Sina Kafiabadi, Jorge Cardoso, Sebastien Ourselin, Tom Vercauteren
2020 Medical Image Analysis  
Brain tissue segmentation from multimodal MRI is a key building block of many neuroimaging analysis pipelines.  ...  However, few existing approaches allow for the joint segmentation of normal tissue and brain lesions.  ...  In addition, the information required for brain tissue or pathology segmentation may come from different scans, leading to hetero-modal (i.e. more than one set of input imaging sequences) datasets.  ... 
doi:10.1016/j.media.2020.101862 pmid:33129151 pmcid:PMC7116853 fatcat:ggpf32trafcy7kcglafkpt2q24

Cardiac MR: From Theory to Practice

Tevfik F. Ismail, Wendy Strugnell, Chiara Coletti, Maša Božić-Iven, Sebastian Weingärtner, Kerstin Hammernik, Teresa Correia, Thomas Küstner
2022 Frontiers in Cardiovascular Medicine  
Basic pulse sequence building blocks that are commonly used in CMR imaging are presented.  ...  Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques.  ...  Image Analysis CMR image segmentation and quantitative evaluation can be a challenging, time-consuming and operator intensive task.  ... 
doi:10.3389/fcvm.2022.826283 pmid:35310962 pmcid:PMC8927633 fatcat:j3vd446nxnajvgajkhazwbvgia

Automated brain lesion segmentation in magnetic resonance images

Simon Andermatt, Philippe Cattin, Jens Thomas Würfel
2019 unpublished
With this thesis, we provide a strong set of tools for the fully automatic segmentation of lesions in brain magnetic resonance imaging (MRI).  ...  Brain Lesion Segmentation in the Literature The body of research of general lesion segmentation in brain MRI is too large to be exhaustively covered in a thesis. Fortunately, Garcia et al.  ...  All lesions were evaluated by the algorithm (including images acquired at 1.5 and 3T MRI field strength). There were no cases that could not be processed by the algorithm.  ... 
doi:10.5451/unibas-007117711 fatcat:jl52hjelwbaebepcevpbx6v2ea

Neuroimaging Biomarkers for Youth At-Risk for Serious Mental Illness [article]

Nikita Nogovitsyn, University Of Calgary, Glenda M. MacQueen, Jean M. Addington
2020
The ultimate aim of this dissertation is to identify neurobiological biomarkers for SMI that will have diagnostic or informative value in the classification of risk stages.  ...  ), I investigate specific structural and functional brain changes accompanying various stages risk and evolution of SMI.  ...  Recent initiatives promoting the development of brain segmentation algorithms 302-305 have resulted in a surge of novel deep learning algorithms 290 (for example MRBrainS 302 , list available online  ... 
doi:10.11575/prism/38095 fatcat:ju4274vw5befhhgwe7er3sfjky