Computational diffusion MRI[electron...
Clark Conference ((2005 :)

 

  • Computational diffusion MRI[electronic resource] :MICCAI Workshop, Munich, Germany, October 9th, 2015 /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 616.07548
    書名/作者: Computational diffusion MRI : MICCAI Workshop, Munich, Germany, October 9th, 2015 // edited by Andrea Fuster ... [et al.].
    其他作者: Fuster, Andrea.
    團體作者: Clark Conference
    出版者: Cham : : Springer International Publishing :, 2016.
    面頁冊數: ix, 234 p. : : ill. (some col.), digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Diffusion magnetic resonance imaging - Congresses.
    標題: Mathematics.
    標題: Visualization.
    標題: Computational Biology/Bioinformatics.
    標題: Computational Science and Engineering.
    標題: Simulation and Modeling.
    標題: Image Processing and Computer Vision.
    標題: Statistics for Life Sciences, Medicine, Health Sciences.
    ISBN: 9783319285887
    ISBN: 9783319285863
    摘要、提要註: These Proceedings of the 2015 MICCAI Workshop "Computational Diffusion MRI" offer a snapshot of the current state of the art on a broad range of topics within the highly active and growing field of diffusion MRI. The topics vary from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms, new computational methods applied to diffusion magnetic resonance imaging data, and applications in neuroscientific studies and clinical practice. Over the last decade interest in diffusion MRI has exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into clinical practice. New processing methods are essential for addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. This volume, which includes both careful mathematical derivations and a wealth of rich, full-color visualizations and biologically or clinically relevant results, offers a valuable starting point for anyone interested in learning about computational diffusion MRI and mathematical methods for mapping brain connectivity, as well as new perspectives and insights on current research challenges for those currently working in the field. It will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics.
    電子資源: http://dx.doi.org/10.1007/978-3-319-28588-7
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