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Steffen Bollmann | Frederik B. Laun | Markus Barth | Kieran O'Brien | Jin Jin | Francesco Cognolato | Simon Robinson | F. Laun | M. Barth | S. Robinson | S. Bollmann | Jin Jin | Kieran O’Brien | Francesco Cognolato
[1] Ferdinand Schweser,et al. Foundations of MRI phase imaging and processing for Quantitative Susceptibility Mapping (QSM). , 2016, Zeitschrift fur medizinische Physik.
[2] Yi Wang,et al. Preconditioned total field inversion (TFI) method for quantitative susceptibility mapping , 2017, Magnetic resonance in medicine.
[3] Bing Wu,et al. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition , 2011, NeuroImage.
[4] Ferdinand Schweser,et al. A comprehensive numerical analysis of background phase correction with V‐SHARP , 2017, NMR in biomedicine.
[5] Tianqi Chen,et al. Empirical Evaluation of Rectified Activations in Convolutional Network , 2015, ArXiv.
[6] Zhe Wu,et al. High resolution myelin water imaging incorporating local tissue susceptibility analysis. , 2017, Magnetic resonance imaging.
[7] Tobias Kober,et al. MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field , 2010, NeuroImage.
[8] P. V. van Zijl,et al. Quantitative Susceptibility Mapping Suggests Altered Brain Iron in Premanifest Huntington Disease , 2016, American Journal of Neuroradiology.
[9] Pascal Spincemaille,et al. Cerebral microbleeds: burden assessment by using quantitative susceptibility mapping. , 2012, Radiology.
[10] Robert Turner,et al. Seven-Tesla Magnetic Resonance Imaging in Wilson Disease Using Quantitative Susceptibility Mapping for Measurement of Copper Accumulation , 2014, Investigative radiology.
[11] José P. Marques,et al. QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures , 2021, Magnetic resonance in medicine.
[12] F. Laun,et al. Quantitative susceptibility mapping depicts severe myelin deficit and iron deposition in a transgenic model of multiple system atrophy , 2020, Experimental Neurology.
[13] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[14] Yi Wang,et al. Multiple sclerosis lesion geometry in quantitative susceptibility mapping (QSM) and phase imaging , 2015, Journal of magnetic resonance imaging : JMRI.
[15] Wotao Yin,et al. An Iterative Regularization Method for Total Variation-Based Image Restoration , 2005, Multiscale Model. Simul..
[16] Kristian Bredies,et al. Fast quantitative susceptibility mapping using 3D EPI and total generalized variation , 2015, NeuroImage.
[17] Yi Wang,et al. Background field removal by solving the Laplacian boundary value problem , 2014, NMR in biomedicine.
[18] Korbinian Eckstein,et al. Phase unwrapping with a rapid opensource minimum spanning tree algorithm (ROMEO) , 2020, bioRxiv.
[19] Jeff H. Duyn,et al. Susceptibility contrast in high field MRI of human brain as a function of tissue iron content , 2009, NeuroImage.
[20] R. Bowtell,et al. Susceptibility mapping in the human brain using threshold‐based k‐space division , 2010, Magnetic resonance in medicine.
[21] Hongjiang Wei,et al. MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping , 2021, NeuroImage.
[22] Xiaojun Guan,et al. Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction , 2019, NeuroImage.
[23] Ferdinand Schweser,et al. Quantitative Susceptibility Mapping in Parkinson's Disease , 2016, PloS one.
[24] Yang Gao,et al. xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks. , 2020, NMR in biomedicine.
[25] Francis Lilley,et al. Fast and robust three-dimensional best path phase unwrapping algorithm. , 2007, Applied optics.
[26] A. Wilman,et al. Background field removal using spherical mean value filtering and Tikhonov regularization , 2014, Magnetic resonance in medicine.
[27] Guy B. Williams,et al. In Vivo Quantitative Susceptibility Mapping (QSM) in Alzheimer's Disease , 2013, PloS one.
[28] Yi Wang,et al. Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: Interpreting positive susceptibility and the presence of iron , 2015, Magnetic resonance in medicine.
[29] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[30] Ferdinand Schweser,et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study , 2012, NeuroImage.
[31] Kevin M. Koch,et al. Deep Quantitative Susceptibility Mapping for Background Field Removal and Total Field Inversion , 2019, 1905.13749.
[32] Mark Jenkinson,et al. Fast, automated, N‐dimensional phase‐unwrapping algorithm , 2003, Magnetic resonance in medicine.
[33] Yi Wang,et al. Morphology enabled dipole inversion (MEDI) from a single‐angle acquisition: Comparison with COSMOS in human brain imaging , 2011, Magnetic resonance in medicine.
[34] Christopher P. Hess,et al. QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field , 2019, NeuroImage.
[35] Thomas Pock,et al. Variational Networks: Connecting Variational Methods and Deep Learning , 2017, GCPR.
[36] Christian Langkammer,et al. DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping , 2019, NeuroImage.
[37] Richard Bowtell,et al. Effects of White Matter Microstructure on Phase and Susceptibility Maps , 2014, Magnetic resonance in medicine.
[38] Richard Bowtell,et al. Whole-brain susceptibility mapping at high field: A comparison of multiple- and single-orientation methods , 2010, NeuroImage.
[39] C. Moonen,et al. A fast calculation method for magnetic field inhomogeneity due to an arbitrary distribution of bulk susceptibility , 2003 .
[40] Julio Acosta-Cabronero,et al. The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design , 2020, Magnetic resonance in medicine.
[41] Ferdinand Schweser,et al. Toward online reconstruction of quantitative susceptibility maps: Superfast dipole inversion , 2013, Magnetic resonance in medicine.
[42] Yi Wang,et al. Calculation of susceptibility through multiple orientation sampling (COSMOS): A method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI , 2009, Magnetic resonance in medicine.
[43] J. Reichenbach,et al. Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. , 2010, Medical physics.
[44] Juan Liu,et al. Deep Gated Convolutional Neural Network for QSM Background Field Removal , 2019, MICCAI.
[45] Julio Acosta-Cabronero,et al. In Vivo MRI Mapping of Brain Iron Deposition across the Adult Lifespan , 2016, The Journal of Neuroscience.
[46] Yan Zhang,et al. Longitudinal change in magnetic susceptibility of new enhanced multiple sclerosis (MS) lesions measured on serial quantitative susceptibility mapping (QSM) , 2016, Journal of magnetic resonance imaging : JMRI.
[47] Sotirios A. Tsaftaris,et al. Medical Image Computing and Computer Assisted Intervention , 2017 .
[48] J. Duyn,et al. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data , 2009, Magnetic resonance in medicine.
[49] Shun Zhang,et al. Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction , 2019, NeuroImage.
[50] Wolfgang Bogner,et al. Combining phase images from array coils using a short echo time reference scan (COMPOSER) , 2015, Magnetic resonance in medicine.
[51] Society of magnetic resonance in medicine , 1990 .
[52] Steffen Bollmann,et al. SHARQnet - Sophisticated Harmonic Artifact Reduction in Quantitative Susceptibility Mapping using a Deep Convolutional Neural Network , 2019, bioRxiv.
[53] Kawin Setsompop,et al. Quantitative susceptibility mapping using deep neural network: QSMnet , 2018, NeuroImage.
[54] Yimei Zhu,et al. Fast phase unwrapping algorithm for interferometric applications. , 2003, Optics letters.
[55] T. Hirai,et al. Clinical quantitative susceptibility mapping (QSM): Biometal imaging and its emerging roles in patient care , 2017, Journal of magnetic resonance imaging : JMRI.
[56] Ferdinand Schweser,et al. Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism? , 2011, NeuroImage.
[57] Xu Li,et al. Learned Proximal Networks for Quantitative Susceptibility Mapping , 2020, MICCAI.
[58] Ferdinand Schweser,et al. Overview of quantitative susceptibility mapping , 2017, NMR in biomedicine.
[59] Steffen Bollmann,et al. Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities , 2019, NMR in biomedicine.
[60] Adrian V. Dalca,et al. A Learning Strategy for Contrast-agnostic MRI Segmentation , 2020, MIDL.
[61] Matthew J. Betts,et al. The whole-brain pattern of magnetic susceptibility perturbations in Parkinson’s disease , 2017, Brain : a journal of neurology.