Computational diffusion MRI : International MICCAI Workshop, Granada, Spain, September 2018 /: International MICCAI Workshop, Granada, Spain, September 2018. ([2019])
- Record Type:
- Book
- Title:
- Computational diffusion MRI : International MICCAI Workshop, Granada, Spain, September 2018 /: International MICCAI Workshop, Granada, Spain, September 2018. ([2019])
- Main Title:
- Computational diffusion MRI : International MICCAI Workshop, Granada, Spain, September 2018
- Further Information:
- Note: Edited by Elisenda Bonet-Carne, Francesco Grussu, Lipeng Ning, Farshid Sepehrband, Chantal M. W. Tax.
- Editors:
- Bonet-Carne, Elisenda
Grussu, Francesco
Ning, Lipeng
Sepehrband, Farshid
Tax, Chantal M. W - Other Names:
- Workshop on Computational Diffusion MRI
International Conference on Medical Image Computing and Computer-Assisted Intervention, 21st - Contents:
- Part I Diffusion MRI Signal Acquisition and Processing Strategies: Towards Optimal Sampling in Diffusion MRI: H. Knutsson.- Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging: I. Rabanillo-Viloria et al.- Return-to_Axis Probability Calculation from Single-Shell Acquisitions: S. Aja-Fernández et al.- A Novel Spatial-Angular Domain Regularisation Approach for Restoration of Diffusion MRI: A. Mella et al.- Dmipy, a Diffusion Microstructure Imaging Toolbox in Python to Improve Research Reproducibility: A. Alimi et al.- Tissue Segmentation Using Sparse Non-Negative Matrix Factorization of Spherical Mean Diffusion MRI Data: P. Sun et al.- A Closed-Form Solution of Rotation Invariant Spherical Harmonic Features in Diffusion MRI: M. Zucchelli et al.- Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization: M. Pizzolato et al.- .- Part II Machine Learning for Diffusion MRI: Crurent Applications and Future Promises of Machine Learning in Diffusion MRI: D. Ravi et al.- q-Space Learning with Synthesized Training Data: C. Ye et al.- Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data: J. Kim et al.- Supervised Classification of White Matter Fibers Based on Neighborhood Fiber Orientation Distributions Using an Ensemble of Neural Networks: D. Ugurlu et al.- .- Part III Diffusion MRI Signal Harmonisation: Challenges and Opportunities in dMRI Data Harmonization: A.H. Zhu et al.-Part I Diffusion MRI Signal Acquisition and Processing Strategies: Towards Optimal Sampling in Diffusion MRI: H. Knutsson.- Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging: I. Rabanillo-Viloria et al.- Return-to_Axis Probability Calculation from Single-Shell Acquisitions: S. Aja-Fernández et al.- A Novel Spatial-Angular Domain Regularisation Approach for Restoration of Diffusion MRI: A. Mella et al.- Dmipy, a Diffusion Microstructure Imaging Toolbox in Python to Improve Research Reproducibility: A. Alimi et al.- Tissue Segmentation Using Sparse Non-Negative Matrix Factorization of Spherical Mean Diffusion MRI Data: P. Sun et al.- A Closed-Form Solution of Rotation Invariant Spherical Harmonic Features in Diffusion MRI: M. Zucchelli et al.- Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization: M. Pizzolato et al.- .- Part II Machine Learning for Diffusion MRI: Crurent Applications and Future Promises of Machine Learning in Diffusion MRI: D. Ravi et al.- q-Space Learning with Synthesized Training Data: C. Ye et al.- Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data: J. Kim et al.- Supervised Classification of White Matter Fibers Based on Neighborhood Fiber Orientation Distributions Using an Ensemble of Neural Networks: D. Ugurlu et al.- .- Part III Diffusion MRI Signal Harmonisation: Challenges and Opportunities in dMRI Data Harmonization: A.H. Zhu et al.- Spherical Harmonic Residual Network for Diffusion Signal Harmonization: S. Koppers et al.- Longitudinal Harmonization for Improving Tractography in Baby Diffusion MRI: K. M. Huynh et al.- Inter-Scanner Harmonization of High Angular Resolution DW-MRI Using Null Space Deep Learning: V. Nath et al.- Effects of Diffusion MRI Model and Harmonization on the Consistency of Findings in an International Multi-Cohort HIV Neuroimaging Study: T.M. Nir et al.- Multi-Shell Diffusion MRI Harmonisation and enhancement Challenge (MUSHAC): Progress and Results: L. Ning et al.- Part IV Diffusion MRI Outside the Brain and Clinical Applications: Diffusion MRI Outside the Brain: R.G. Nunes et al.- A Framework for Calculating Time-Efficient Diffusion MRI Protocols for Anisotropic IVIM and an Application in the Placenta: P.J. Slator et al.- Spatial Characterisation of Fibre Response Functions for Spherical Deconvolution in Multiple Sclerosis: C. Tur et al.- Edge Weights and Network Properties in Multiple Sclerosis: E. Powell et al.- Part V Tractography and Connectivity Mapping: Measures of Tractography Convergence: D.C. Moyer et al.- Brain Connectivity Measures via Direct Sub-Finslerian Front Propagation on the 5D Sphere Bundle of Positions and Directions: J. Portegies et al.- Inference of an Extended Short Fiber Bundle Atlas Using Sulcus-Based Constraints for a Diffeomorphic Inter-Subject Alignment: N.L. Avila et al.- Resolving the Crossing/Kissing Fiber Ambiguity Using Functionally Informed COMMIT: M. Frigo et al.- Voxel-Wise Clustering of Tractography Data for Building Atlases of Local Fiber Geometry: I. Brusini et al.- Obtaining Representative Core Streamlines for White Matter Tractometry of the Human Brain: M. Chamberland et al.- Improving Graph-Based Tractography Plausibility Using Microstructure Information: M. Battocchio et al.- Deterministic Group Tractography with Local Uncertainty Quantification: A.N. Holm et al.- Index. … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2019
- Extent:
- 1 online resource (xii, 390 pages), illustrations (some color)
- Subjects:
- 616.07/548
Diffusion magnetic resonance imaging -- Congresses
Electronic books - Languages:
- English
- ISBNs:
- 9783030058319
- Related ISBNs:
- 303005831X
9783030058302 - Notes:
- Note: Online resource; title from PDF title page (SpringerLink, viewed May 13, 2019).
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