Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks
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Jaeil Kim | Dinggang Shen | Geng Chen | Yongqin Zhang | Weili Lin | Jiquan Ma | Khoi Minh Huynh | Pew-Thian Yap | Yoonmi Hong | Weili Lin | D. Shen | P. Yap | Yongqin Zhang | Geng Chen | Jaeil Kim | Yoonmi Hong | Jiquan Ma
[1] Dinggang Shen,et al. Multifold Acceleration of Diffusion MRI via Deep Learning Reconstruction from Slice-Undersampled Data , 2019, IPMI.
[2] J. Helpern,et al. Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.
[3] Dinggang Shen,et al. Noise reduction in diffusion MRI using non‐local self‐similar information in joint Symbol space , 2018, Medical Image Anal..
[4] Dinggang Shen,et al. XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI , 2019, Medical Image Anal..
[5] Pew-Thian Yap,et al. Longitudinal Prediction of Infant Diffusion MRI Data via Graph Convolutional Adversarial Networks , 2019, IEEE Transactions on Medical Imaging.
[6] Zhiwei Li,et al. Fast and Robust Diffusion Kurtosis Parametric Mapping Using a Three-Dimensional Convolutional Neural Network , 2019, IEEE Access.
[7] Dawn Fallik. The Human Connectome Project Turns to Mapping Brain Development, from Birth through Early Childhood , 2016 .
[8] Chuyang Ye,et al. Tissue microstructure estimation using a deep network inspired by a dictionary‐based framework , 2017, Medical Image Anal..
[9] Ganesh Adluru,et al. Simultaneous NODDI and GFA parameter map generation from subsampled q‐space imaging using deep learning , 2018, Magnetic resonance in medicine.
[10] Pew-Thian Yap,et al. Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks , 2019, MICCAI.
[11] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.
[12] Daichi Sone,et al. Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy , 2019, Reports in Medical Imaging.
[13] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[14] Chuyang Ye,et al. An improved deep network for tissue microstructure estimation with uncertainty quantification , 2020, Medical Image Anal..
[15] Yong Zhang,et al. Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q Space , 2019, IEEE Transactions on Medical Imaging.
[16] Essa Yacoub,et al. The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.
[17] Kim-Han Thung,et al. Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging , 2019, IEEE Transactions on Medical Imaging.
[18] Chenghao Liu,et al. Super-Resolved q-Space Deep Learning , 2019, MICCAI.
[19] Timothy Edward John Behrens,et al. Diffusion MRI : from quantitative measurement to in vivo neuroanatomy , 2014 .
[20] Weili Lin,et al. Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data , 2019 .
[21] Jean-Philippe Thiran,et al. Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data , 2015, NeuroImage.
[22] F. Kruggel,et al. Quantitative mapping of the per‐axon diffusion coefficients in brain white matter , 2015, Magnetic resonance in medicine.
[23] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[24] Chuyang Ye,et al. A deep network for tissue microstructure estimation using modified LSTM units , 2019, Medical Image Anal..
[25] Daniel C. Alexander,et al. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.
[26] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Dinggang Shen,et al. The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development , 2019, NeuroImage.
[28] J. Thiran,et al. Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. , 2006, Radiographics : a review publication of the Radiological Society of North America, Inc.
[29] Daniel Cremers,et al. q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans , 2016, IEEE Transactions on Medical Imaging.
[30] Kim-Han Thung,et al. Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments , 2019, MICCAI.