Archive (2016–2006)

MITK Diffusion Imaging

Journal: Methods of Information in Medicine
Subtitle: A journal stressing, for more than 50 years, the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care
ISSN: 0026-1270
Topic:

Focus Theme
Image Analysis and Modeling in Medical Image Computing
Guest Editors: H. Handels, T. M. Deserno, H.-P. Meinzer, T. Tolxdorff

DOI: https://doi.org/10.3414/ME11-02-0031
Issue: 2012 (Vol. 51): Issue 5 2012
Pages: 441-448

MITK Diffusion Imaging

Focus Theme - Image Analysis and Modeling in Medical Image Computing

K. H. Fritzsche (1, 2), P. F. Neher (1), I. Reicht (1), T. van Bruggen (1), C. Goch (1), M. Reisert (3), M. Nolden (1), S. Zelzer (1), H.-P. Meinzer (1), B. Stieltjes (2)

(1) German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany; (2) German Cancer Research Center, Section Quantitative Imaging-based Disease Characterization, Heidelberg, Germany; (3) University Hospital Freiburg, Department of Radiology, Medical Physics, Freiburg, Germany

Keywords

tractography, Diffusion tensor imaging, Q-ball imaging, open-source software toolkit, common toolkit CTK

Summary

Background: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets. Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field. Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITK-DI, are demonstrated using in-vivo datasets. Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use installable application. Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

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