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Proceedings Paper

A C++ framework for creating tissue specific segmentation-pipelines
Author(s): Bernhard Pfeifer; Friedrich Hanser; Michael Seger; Christoph Hintermueller; Robert Modre-Osprian; Gerald Fischer; Hannes Muehlthaler; Thomas Trieb; Bernhard Tilg
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Paper Abstract

For a clinical application of the inverse problem of electrocardiography, a flexible and fast generation of a patient's volume conductor model is essential. The volume conductor model includes compartments like chest, lungs, ventricles, atria and the associated blood masses. It is a challenging task to create an automatic or semi-automatic segmentation procedure for each compartment. For the extraction of the lungs, as one example, a region growing algorithm can be used, to extract the blood masses of the ventricles Active Appearance Models may succeed, and to construct the atrial myocardium a multiplicity of operations are necessary. These examples illustrate that there is no common method that will succeed for all compartments like a least common denominator. Another problem is the automatization of combining different methods and the origination of a segmentation pipeline in order to extract a compartment and, accordingly, the desired model - in our case the complete volume conductor model for estimating the spread of electrical excitation in the patient's heart. On account of this, we developed a C++ framework and a special application with the goal of creating tissue-specific segmentation pipelines. The C++ framework uses different standard frameworks like DCMTK for handling medical images (http://dicom.offis.de/dcmtk.php.en), ITK (http://www.itk.org/) for some segmentation methods, and Qt (http://www.trolltech.com/) for creating user interfaces. Our Medical Segmentation Toolkit (MST) enables to combine different segmentation techniques for each compartment. In addition, the framework enables to create user-defined compartment pipelines.

Paper Details

Date Published: 12 April 2005
PDF: 12 pages
Proc. SPIE 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, (12 April 2005); doi: 10.1117/12.591915
Show Author Affiliations
Bernhard Pfeifer, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Friedrich Hanser, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Michael Seger, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Christoph Hintermueller, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Robert Modre-Osprian, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Gerald Fischer, Univ. for Health Sciences, Medical Informatics and Technology (Austria)
Hannes Muehlthaler, Innsbruck Medical Univ. (Austria)
Thomas Trieb, Innsbruck Medical Univ. (Austria)
Bernhard Tilg, Univ. for Health Sciences, Medical Informatics and Technology (Austria)


Published in SPIE Proceedings Vol. 5744:
Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display
Robert L. Galloway Jr.; Kevin R. Cleary, Editor(s)

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