MITK Diffusion Imaging

K. H. Fritzsche; P. F. Neher; I. Reicht; T. van Bruggen; C. Goch; M. Reisert; M. Nolden; S. Zelzer; H.-P. Meinzer; B. Stieltjes

doi:10.3414/ME11-02-0031

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 2012; 51(05): 441-448
DOI: 10.3414/ME11-02-0031

Focus Theme – Original Articles

Schattauer GmbH

MITK Diffusion Imaging

K. H. Fritzsche

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

²German Cancer Research Center, Section Quantitative Imaging-based Disease Characterization, Heidelberg, Germany

,

P. F. Neher

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

I. Reicht

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

T. van Bruggen

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

C. Goch

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

M. Reisert

³University Hospital Freiburg, Department of Radiology, Medical Physics, Freiburg, Germany

,

M. Nolden

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

S. Zelzer

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

H.-P. Meinzer

¹German Cancer Research Centre, Division of Medical and Biological Informatics, Heidelberg, Germany

,

B. Stieltjes

²German Cancer Research Center, Section Quantitative Imaging-based Disease Characterization, Heidelberg, Germany

› Institutsangaben

Abstract

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), MITKDI, 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 in stallable 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.

Keywords

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

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Referenzen

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