A C++ framework for creating tissue specific segmentation-pipelines

Bernhard Pfeifer; Friedrich Hanser; Michael Seger; Christoph Hintermueller; Robert Modre-Osprian; Gerald Fischer; Hannes Muehlthaler; Thomas Trieb; Bernhard Tilg

doi:10.1117/12.591915

12 April 2005 A C++ framework for creating tissue specific segmentation-pipelines

Bernhard Pfeifer, Friedrich Hanser, Michael Seger, Christoph Hintermueller, Robert Modre-Osprian, Gerald Fischer, Hannes Muehlthaler, Thomas Trieb, Bernhard Tilg

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Proceedings Volume 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display; (2005) https://doi.org/10.1117/12.591915
Event: Medical Imaging, 2005, San Diego, California, United States

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.

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Bernhard Pfeifer, Friedrich Hanser, Michael Seger, Christoph Hintermueller, Robert Modre-Osprian, Gerald Fischer, Hannes Muehlthaler, Thomas Trieb, and Bernhard Tilg "A C++ framework for creating tissue specific segmentation-pipelines", Proc. SPIE 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, (12 April 2005); https://doi.org/10.1117/12.591915

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KEYWORDS

Image segmentation

Image processing

C++

Tissues

Blood

Lung

Image processing algorithms and systems

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