Download Computational Diffusion MRI: MICCAI Workshop, Munich, by Andrea Fuster, Aurobrata Ghosh, Enrico Kaden, Yogesh Rathi, PDF

By Andrea Fuster, Aurobrata Ghosh, Enrico Kaden, Yogesh Rathi, Marco Reisert

These court cases of the 2015 MICCAI Workshop “Computational Diffusion MRI” provide a photo of the present cutting-edge on a huge diversity of themes in the hugely energetic and starting to be box of diffusion MRI. the themes range from basic theoretical paintings on mathematical modeling, to the improvement and overview of sturdy algorithms, new computational equipment utilized to diffusion magnetic resonance imaging facts, and purposes in neuroscientific reports and medical practice.

during the last decade curiosity in diffusion MRI has exploded. The process presents particular insights into the microstructure of dwelling tissue and allows in-vivo connectivity mapping of the mind. Computational strategies are key to the continuing good fortune and improvement of diffusion MRI and to its common move into medical perform. New processing tools are crucial for addressing concerns at every one level of the diffusion MRI pipeline: acquisition, reconstruction, modeling and version becoming, snapshot processing, fiber monitoring, connectivity mapping, visualization, staff experiences and inference.

This quantity, together with either cautious mathematical derivations and a wealth of wealthy, full-color visualizations and biologically or clinically appropriate effects, deals a important place to begin for a person drawn to studying approximately computational diffusion MRI and mathematical tools for mapping mind connectivity, in addition to new views and insights on present examine demanding situations for these presently operating within the box. it is going to be of curiosity to researchers and practitioners within the fields of laptop technology, MR physics, and utilized mathematics.​

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Additional resources for Computational Diffusion MRI: MICCAI Workshop, Munich, Germany, October 9th, 2015

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Regions were grouped into six lobes (Fig. 2a): frontal, parietal, temporal, occipital, insular, and cingulate cortex. Fig. 1 Automatically segmented regions of interest (ROIs). (a) Thirty-four cortical regions were parcellated in each hemisphere from the T1-MDT using FreeSurfer and grouped into six bilateral cortical lobes. (b) Seven bilateral subcortical structures were segmented from the T1-MDT with FSL FIRST. (c) Twenty-one major white matter tracts from the JHU atlas were elastically registered to the FA-MDT.

Med. 74(4), 1019–1031 (2015) 6. : Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn. Reson. Med. 72, 707–717 (2014) 7. : Fast reconstruction for multichannel compressed sensing using a hierarchically semiseparable solver. Magn. Reson. Med. 73, 1034–1040 (2015) 8. : Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data.

4 Discussion The results of holistic reconstruction demonstrate considerably more detail than the standard reconstruction. Among the numerous advanced diffusion MRI reconstruction methods existing in literature, many methods perform denoising, missing data reconstruction (q-space compressed sensing), enhancement, etc. as an intermediate post-processing step after image-space reconstruction. g. Rician or more complicated), and irretrievably discard some parts of information present in the raw k-space data.

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