Computational Diffusion MRI
Springer International Publishing (Verlag)
978-3-319-28586-3 (ISBN)
TheseProceedings of the 2015 MICCAI Workshop "Computational Diffusion MRI" offer asnapshot of the current state of the art on a broad range of topics within thehighly active and growing field of diffusion MRI. The topics vary fromfundamental theoretical work on mathematical modeling, to the development andevaluation of robust algorithms, new computational methods applied to diffusionmagnetic resonance imaging data, and applications in neuroscientific studiesand clinical practice.
Over thelast decade interest in diffusion MRI has exploded. The technique providesunique insights into the microstructure of living tissue and enables in-vivoconnectivity mapping of the brain. Computational techniques are key to thecontinued success and development of diffusion MRI and to its widespreadtransfer into clinical practice. New processing methods are essential for addressingissues at each stage of the diffusion MRI pipeline: acquisition, reconstruction,modeling and model fitting, image processing, fiber tracking, connectivitymapping, visualization, group studies and inference.Thisvolume, which includes both careful mathematical derivations and a wealth ofrich, full-color visualizations and biologically or clinically relevantresults, offers a valuable starting point for anyone interested in learningabout computational diffusion MRI and mathematical methods for mapping brainconnectivity, as well as new perspectives and insights on current researchchallenges for those currently working in the field. It will be of interest toresearchers and practitioners in the fields of computer science, MR physics,and applied mathematics.
An Efficient FiniteElement Solution of the Generalised Bloch-Torrey Equation for ArbitraryDomains: L. Beltrachini et al.- Super-Resolution Reconstruction ofDiffusion-Weighted Images using 4D Low-Rank and Total Variation: Feng Shi etal.- Holistic Image Reconstruction for Diffusion MRI: V. Golkov et al.- Alzheimer'sDisease Classification with Novel Microstructural Metrics fromDiffusion-Weighted MRI: T. M. Nir et al.- Brain Tissue Micro-Structure Imagingfrom Diffusion MRI Using Least Squares Variable Separation: H. Farooq et al.-Multi-Tensor MAPMRI: How to Estimate Microstructural Information from CrossingFibers: M. Zucchelli et al.- On the Use of Antipodal Optimal DimensionalitySampling Scheme on the Sphere for Recovering Intra-Voxel Fibre Structure inDiffusion MRI: A.P. Bates et al.- Estimation of Fiber Orientations UsingNeighborhood Information: C. Ye et al.- A framework for creating populationspecific multimodal brain atlas using clinical T1 and diffusion tensor images:V. Gupta et al.- Alignment of Tractograms as Linear Assignment Problem: N. Sharmin.-Accelerating Global Tractography Using Parallel Markov Chain Monte Carlo: H. Wuet al.- Adaptive Enhancement in Diffusion MRI Through Propagator Sharpening: T.Dela Haije et al.- Angular Resolution Enhancement of Diffusion MRI Data UsingInter-Image Information Transfer: Geng Chen et al.- Crossing versus Fanning:Model Comparison Using HCP Data: A. Ghosh et al.- White Matter Fiber SetSimplification by Redundancy Reduction with Minimum Anatomical InformationLoss: G. Zimmerman Moreno et al.- A Temperature Phantom to Probe the EnsembleAverage Propagator Asymmetry: an In-Silico Study: M. Pizzolato et al.-Registration Strategies for Whole-Body Diffusion-Weighted MRI Stitching: J.Ceranka et al.- HARDI Feature Selection, Registration and Atlas Building forA$beta$ Pathology Classification: E. Schwab et al.- Reliability of StructuralConnectivity Examined with Four Different Diffusion Reconstruction Methods atTwo Different Spatial and Angular Resolutions: J. E. Villalon-Reina et al.
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | Mathematics and Visualization |
| Zusatzinfo | IX, 234 p. 83 illus., 63 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Software Entwicklung ► User Interfaces (HCI) |
| Mathematik / Informatik ► Mathematik ► Graphentheorie | |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | brain network analysis • Computational Biology/Bioinformatics • computational science and engineering • Connectomics • diffusion tensor imaging • Fiber Tractography • Image Processing • image processing and computer vision • Inverse Problems • Magnetic Resonance Imaging • mathematics and statistics • Medical Image Analysis • neuroimaging • Segmentation • Simulation and modeling • Statistics for Life Sciences, Medicine, Health Sci • Visualization |
| ISBN-10 | 3-319-28586-6 / 3319285866 |
| ISBN-13 | 978-3-319-28586-3 / 9783319285863 |
| Zustand | Neuware |
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