Computational Diffusion MRI

Part I Data Acquisition and Modeling: Estimating Tissue Microstructure using Diffusion-Weighted Magnetic Resonance Spectroscopy of Brain Metabolites by Marco Palombo.- (k, q)-Compressed Sensing for dMRI with Joint Spatial-Angular Sparsity Prior by Evan Schwab et al.- Spatio-Temporal dMRI Acquisition Design: Reducing the Number of q Samples Through a Relaxed Probabilistic Model by Patryk Filipiak et al.- A Generalized SMT-Based Framework for Diffusion MRI Microstructural Model Estimation by Mauro Zucchelli et al.- Part II Image Postprocessing: Diffusion Specific Segmentation: Skull Stripping with Diffusion MRIData Alone by Robert I. Reid et al.- Diffeomorphic Registration of Diffusion Mean Apparent Propagator Fields Using Dynamic Programming on a Minimum Spanning Tree by K´evin Ginsburger et al.- Diffusion Orientation Histograms (DOH) for Diffusion Weighted Image Analysis by Laurent Chauvin et al.- Part III Tractography and Connectivity: Learning aSingle Step of Streamline Tractography Based on Neural Networks by Daniel Jörgens et al.- Probabilistic Tractography for Complex Fiber Orientations with Automatic Model Selection by Edwin Versteeg et al.- Bundle-Specific Tractography by Francois Rheault et al.- A Sheet Probability Index from Diffusion Tensor Imaging by Michael Ankele et al.- Recovering Missing Connections in Diffusion Weighted MRI Using Matrix Completion by Chendi Wang et al.- Brain Parcellation and Connectivity Mapping Using Wasserstein Geometry by Hamza Farooq et al.- Exploiting Machine Learning Principles for Assessing the Fingerprinting Potential of Connectivity Features by Silvia Obertino et al.- Part IV Clinical Applications: Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players by Itay Benou et al.- Longitudinal Analysis Framework of DWI Data for Reconstructing Structural Brain Networks with Application to