Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
暂无分享,去创建一个
Wiro J. Niessen | Marion Smits | M. Arfan Ikram | Meike W. Vernooij | Bo Li | Marius de Groot | Rebecca M. E. Steketee | Rozanna Meijboom | Jiren Liu | Esther E. Bron | W. Niessen | M. Vernooij | M. Ikram | E. Bron | M. Smits | M. Groot | R. Meijboom | R. Steketee | Jiren Liu | Bo Li
[1] Paul M. Thompson,et al. Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics , 2014, NeuroImage.
[2] Bo Li,et al. Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset , 2018, MLMI@MICCAI.
[3] Martin Styner,et al. TRAFIC: fiber tract classification using deep learning , 2018, Medical Imaging.
[4] Michael Brady,et al. Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.
[5] Maxime Descoteaux,et al. Recognition of white matter bundles using local and global streamline-based registration and clustering , 2017, NeuroImage.
[6] Nick C Fox,et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. , 2011, Brain : a journal of neurology.
[7] Derek K. Jones,et al. The effect of filter size on VBM analyses of DT-MRI data , 2005, NeuroImage.
[8] Arthur W. Toga,et al. Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer's disease participants , 2009, NeuroImage.
[9] Wiro Niessen,et al. A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes , 2019, MICCAI.
[10] C. Tappert,et al. A Survey of Binary Similarity and Distance Measures , 2010 .
[11] Wiro J. Niessen,et al. White matter atrophy and lesion formation explain the loss of structural integrity of white matter in aging , 2008, NeuroImage.
[12] Paul M. Thompson,et al. Fibernet 2.0: An Automatic Neural Network Based Tool for Clustering White Matter Fibers in the Brain , 2017, bioRxiv.
[13] Maxime Descoteaux,et al. Tractography and machine learning: Current state and open challenges , 2019, Magnetic resonance imaging.
[14] Stephen M. Smith,et al. Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes , 2018, NeuroImage.
[15] Wiro J. Niessen,et al. Tract-specific white matter degeneration in aging: The Rotterdam Study , 2015, Alzheimer's & Dementia.
[16] Wiro J. Niessen,et al. Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification , 2007, NeuroImage.
[17] Randy L. Gollub,et al. Reproducibility of quantitative tractography methods applied to cerebral white matter , 2007, NeuroImage.
[18] Thomas R. Barrick,et al. Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection , 2008, NeuroImage.
[19] Jan Sijbers,et al. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data , 2009 .
[20] P. Szeszko,et al. MRI atlas of human white matter , 2006 .
[21] Peter F. Neher,et al. Learn to Track: Deep Learning for Tractography , 2017, bioRxiv.
[22] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[23] Simon K. Warfield,et al. Automated delineation of white matter fiber tracts with a multiple region-of-interest approach , 2012, NeuroImage.
[24] Bruce Fischl,et al. Joint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors , 2016, NeuroImage.
[25] Stefan Klein,et al. Improving alignment in Tract-based spatial statistics: Evaluation and optimization of image registration , 2013, NeuroImage.
[26] Peter F. Neher,et al. TractSeg - Fast and accurate white matter tract segmentation , 2018, NeuroImage.
[27] Carl-Fredrik Westin,et al. The white matter query language: a novel approach for describing human white matter anatomy , 2015, Brain Structure and Function.
[28] Alexandra J. Golby,et al. Deep White Matter Analysis: Fast, Consistent Tractography Segmentation Across Populations and dMRI Acquisitions , 2019, MICCAI.
[29] 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).
[30] Tonya White,et al. White matter ‘potholes’ in early-onset schizophrenia: A new approach to evaluate white matter microstructure using diffusion tensor imaging , 2009, Psychiatry Research: Neuroimaging.
[31] R. Laforce. Behavioral and language variants of frontotemporal dementia: A review of key symptoms , 2013, Clinical Neurology and Neurosurgery.
[32] Monique M. B. Breteler,et al. The Rotterdam Study: 2016 objectives and design update , 2015, European Journal of Epidemiology.
[33] Terry M. Peters,et al. 3D statistical neuroanatomical models from 305 MRI volumes , 1993, 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference.
[34] Derek K. Jones,et al. White matter organization in developmental coordination disorder: A pilot study exploring the added value of constrained spherical deconvolution , 2018, NeuroImage: Clinical.
[35] F. Crick,et al. Backwardness of human neuroanatomy , 1993, Nature.
[36] Tomas Jonsson,et al. The dimensionality of between‐person differences in white matter microstructure in old age , 2013, Human brain mapping.
[37] Haruyasu Yamada,et al. Normal aging in the central nervous system: quantitative MR diffusion-tensor analysis , 2002, Neurobiology of Aging.
[38] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[39] Carl-Fredrik Westin,et al. A comparison of three fiber tract delineation methods and their impact on white matter analysis , 2018, NeuroImage.
[40] Jerry L. Prince,et al. Direct segmentation of the major white matter tracts in diffusion tensor images , 2011, NeuroImage.
[41] Matthias J. Müller,et al. Color-coded diffusion-tensor-imaging of posterior cingulate fiber tracts in mild cognitive impairment , 2005, Neurobiology of Aging.
[42] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[43] D. Mantini,et al. Exploring quantitative group-wise differentiation of Alzheimer’s disease and behavioural variant frontotemporal dementia using tract-specific microstructural white matter and functional connectivity measures at multiple time points , 2019, European Radiology.
[44] Timothy Dozat,et al. Incorporating Nesterov Momentum into Adam , 2016 .
[45] Peter A. Calabresi,et al. Tract probability maps in stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification , 2008, NeuroImage.
[46] Kaiming Li,et al. Automatic clustering of white matter fibers based on symbolic sequence analysis , 2010, Medical Imaging.
[47] Mark W. Woolrich,et al. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.
[48] Wiro J Niessen,et al. Global and focal white matter integrity in breast cancer survivors 20 years after adjuvant chemotherapy , 2014, Human brain mapping.
[49] Anqi Qiu,et al. Multi-label segmentation of white matter structures: Application to neonatal brains , 2014, NeuroImage.
[50] Marion Smits,et al. Early-stage differentiation between presenile Alzheimer’s disease and frontotemporal dementia using arterial spin labeling MRI , 2015, European Radiology.
[51] S. Wakana,et al. Fiber tract-based atlas of human white matter anatomy. , 2004, Radiology.
[52] J. Morris,et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.
[53] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[54] Arnav Bhavsar,et al. FS2Net: Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation Using Stacked LSTM Based Siamese Network , 2019, CAIP.
[55] Seyed-Ahmad Ahmadi,et al. Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound , 2016, Comput. Vis. Image Underst..
[56] J. R. Landis,et al. The measurement of observer agreement for categorical data. , 1977, Biometrics.
[57] Mark W. Woolrich,et al. FSL , 2012, NeuroImage.
[58] Pew-Thian Yap,et al. DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks , 2019, GLMI@MICCAI.
[59] Carl-Fredrik Westin,et al. Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas , 2007, IEEE Transactions on Medical Imaging.
[60] Klaus H. Maier-Hein,et al. nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation , 2018, Bildverarbeitung für die Medizin.
[61] Max A. Viergever,et al. elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.
[62] Stephen M. Smith,et al. Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.
[63] Brian B. Avants,et al. High-Dimensional Spatial Normalization of Diffusion Tensor Images Improves the Detection of White Matter Differences: An Example Study Using Amyotrophic Lateral Sclerosis , 2007, IEEE Transactions on Medical Imaging.
[64] Alan Connelly,et al. Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution , 2007, NeuroImage.
[65] Christophe Lenglet,et al. Automatic clustering and population analysis of white matter tracts using maximum density paths , 2014, NeuroImage.
[66] Daniel Rueckert,et al. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data , 2006, NeuroImage.
[67] Peter F. Neher,et al. The challenge of mapping the human connectome based on diffusion tractography , 2017, Nature Communications.
[68] P. Ellen Grant,et al. TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain , 2019, NeuroImage.
[69] S. Wakana,et al. MRI Atlas of Human White Matter , 2005 .
[70] Samuel Powell,et al. Reliability and Repeatability of Quantitative Tractography Methods for Mapping Structural White Matter Connectivity in Preterm and Term Infants at Term-Equivalent Age , 2014, PloS one.
[71] Timothy Edward John Behrens,et al. Characterization and propagation of uncertainty in diffusion‐weighted MR imaging , 2003, Magnetic resonance in medicine.