Automated brain extraction of multisequence MRI using artificial neural networks
暂无分享,去创建一个
Klaus H. Maier-Hein | David Bonekamp | Fabian Isensee | Martin Bendszus | Marianne Schell | Sabine Heiland | Irada Pflueger | Gianluca Brugnara | Ulf Neuberger | Antje Wick | Heinz Peter Schlemmer | Wolfgang Wick | Philipp Kickingereder
[1] Jerry L. Prince,et al. Cortical reconstruction using implicit surface evolution: Accuracy and precision analysis , 2006, NeuroImage.
[2] Patrick van der Smagt,et al. CNN-based Segmentation of Medical Imaging Data , 2017, ArXiv.
[3] Konstantinos Kamnitsas,et al. Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation , 2016, Medical Image Anal..
[4] Jeffrey N. Chiang,et al. Optimized Brain Extraction for Pathological Brains (optiBET) , 2014, PloS one.
[5] Allan Hanbury,et al. An Efficient Algorithm for Calculating the Exact Hausdorff Distance , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Li Wang,et al. Level set segmentation of brain magnetic resonance images based on local Gaussian distribution fitting energy , 2010, Journal of Neuroscience Methods.
[7] Ulla Ruotsalainen,et al. Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: Adaptive disconnection algorithm , 2010, Medical Image Anal..
[8] Heinz-Otto Peitgen,et al. The Skull Stripping Problem in MRI Solved by a Single 3D Watershed Transform , 2000, MICCAI.
[9] Nikolaos Papanikolopoulos,et al. Imperfect Segmentation Labels: How Much Do They Matter? , 2018, CVII-STENT/LABELS@MICCAI.
[10] Guido Gerig,et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.
[11] H. Haidar,et al. Measurement of Cortical Thickness in 3D Brain MRI Data: Validation of the Laplacian Method , 2006, Journal of neuroimaging : official journal of the American Society of Neuroimaging.
[12] W. A. Hanson,et al. Interactive 3D segmentation of MRI and CT volumes using morphological operations. , 1992, Journal of computer assisted tomography.
[13] R. Leahy,et al. Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.
[14] Xu Han,et al. Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach , 2017, NeuroImage.
[15] Peter König,et al. Data augmentation instead of explicit regularization , 2018, ArXiv.
[16] Bruce Fischl,et al. Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.
[17] Jacoline E. C. Bromberg,et al. Phase II part of EORTC study 26101: The sequence of bevacizumab and lomustine in patients with first recurrence of a glioblastoma. , 2016 .
[18] Mark W. Woolrich,et al. Bayesian analysis of neuroimaging data in FSL , 2009, NeuroImage.
[19] D Louis Collins,et al. An efficient and accurate method for robust inter‐dataset brain extraction and comparisons with 9 other methods , 2018, Human brain mapping.
[20] Alan C. Evans,et al. Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.
[21] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[22] Martin Klein,et al. Lomustine and Bevacizumab in Progressive Glioblastoma , 2017, The New England journal of medicine.
[23] Snehashis Roy,et al. Robust skull stripping using multiple MR image contrasts insensitive to pathology , 2017, NeuroImage.
[24] Seyed-Ahmad Ahmadi,et al. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[25] Bruce R. Rosen,et al. DeepNeuro: an open-source deep learning toolbox for neuroimaging , 2018, Neuroinformatics.
[26] Jacob Cohen. Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.
[27] Stephen M. Smith,et al. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.
[28] D. Louis Collins,et al. BEaST: Brain extraction based on nonlocal segmentation technique , 2012, NeuroImage.
[29] Anders M. Dale,et al. Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.
[30] Ludwig Kappos,et al. Correlation between brain volume loss and clinical and MRI outcomes in multiple sclerosis , 2015, Neurology.
[31] J. Mazziotta,et al. MRI‐PET Registration with Automated Algorithm , 1993, Journal of computer assisted tomography.
[32] Arthur W. Toga,et al. Construction of a 3D probabilistic atlas of human cortical structures , 2008, NeuroImage.
[33] Klaus H. Maier-Hein,et al. Deep MRI brain extraction: A 3D convolutional neural network for skull stripping , 2016, NeuroImage.
[34] Guido Gerig,et al. Elastic model-based segmentation of 3-D neuroradiological data sets , 1999, IEEE Transactions on Medical Imaging.
[35] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[36] Stephen M. Smith,et al. A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..
[37] L. R. Dice. Measures of the Amount of Ecologic Association Between Species , 1945 .
[38] Nick C Fox,et al. The clinical use of structural MRI in Alzheimer disease , 2010, Nature Reviews Neurology.
[39] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[40] Gregory G. Brown,et al. Quantitative evaluation of automated skull‐stripping methods applied to contemporary and legacy images: Effects of diagnosis, bias correction, and slice location , 2006, Human brain mapping.
[41] Deniz Erdogmus,et al. Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging , 2017, IEEE Transactions on Medical Imaging.
[42] Richard M. Leahy,et al. BrainSuite: An Automated Cortical Surface Identification Tool , 2000, MICCAI.
[43] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[44] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.
[45] Yi Hong,et al. CompNet: Complementary Segmentation Network for Brain MRI Extraction , 2018, MICCAI.
[46] P. Kalavathi,et al. Methods on Skull Stripping of MRI Head Scan Images—a Review , 2016, Journal of Digital Imaging.
[47] R Cameron Craddock,et al. The preprocessed connectomes project repository of manually corrected skull-stripped T1-weighted anatomical MRI data , 2016, bioRxiv.
[48] Sébastien Ourselin,et al. Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations , 2017, DLMIA/ML-CDS@MICCAI.
[49] Richard Frayne,et al. An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement , 2017, NeuroImage.
[50] Christopher Joseph Pal,et al. Brain tumor segmentation with Deep Neural Networks , 2015, Medical Image Anal..
[51] Jian Chen,et al. Brain extraction using the watershed transform from markers , 2013, Front. Neuroinform..
[52] Wiro J. Niessen,et al. Accuracy and reproducibility study of automatic MRI brain tissue segmentation methods , 2010, NeuroImage.
[53] David Bonekamp,et al. Automated brain extraction of multisequence MRI using artificial neural networks , 2019, Human brain mapping.
[54] Satrajit S. Ghosh,et al. Evaluation of volume-based and surface-based brain image registration methods , 2010, NeuroImage.
[55] R W Cox,et al. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.
[56] Rita G. Nunes,et al. Reconstruction of white matter fibre tracts using diffusion kurtosis tensor imaging at 1.5T: Pre-surgical planning in patients with gliomas , 2018, European journal of radiology open.
[57] S. Heiland,et al. Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study. , 2019, The Lancet. Oncology.
[58] Fang Liu,et al. Bayesian convolutional neural network based MRI brain extraction on nonhuman primates , 2018, NeuroImage.
[59] Paul M. Thompson,et al. Robust Brain Extraction Across Datasets and Comparison With Publicly Available Methods , 2011, IEEE Transactions on Medical Imaging.
[60] Mark Jenkinson,et al. Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis , 2012, NeuroImage.
[61] Klaus H. Maier-Hein,et al. Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge , 2017, BrainLes@MICCAI.
[62] Brian B. Avants,et al. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) , 2015, IEEE Transactions on Medical Imaging.