Mr. Jan Rexilius Profile

Jan Rexilius

at Fraunhofer MEVIS

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Author

Publications (9)

Proceedings Article | 4 March 2009 Paper

Objective tumour heterogeneity determination in gliomas

Dirk Simon, Jan Klein, Jan Rexilius, Bram Stieltjes

Proceedings Volume 7260, 72601X (2009) https://doi.org/10.1117/12.812521

KEYWORDS: Expectation maximization algorithms, Tissues, Diffusion, Diffusion weighted imaging, Brain, Radiotherapy, Tumor growth modeling, Software development, Statistical modeling, Binary data

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Proceedings Article | 26 March 2008 Paper

Towards user-independent DTI quantification

Jan Klein, Hannes Stuke, Jan Rexilius, Bram Stieltjes, Horst Hahn, Heinz-Otto Peitgen

Proceedings Volume 6914, 69142E (2008) https://doi.org/10.1117/12.768763

KEYWORDS: Diffusion tensor imaging, Tissues, 3D image processing, 3D image reconstruction, Brain, Image processing, Algorithm development, Anisotropy, Detection and tracking algorithms, Medical research

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Quantification of diffusion tensor imaging (DTI) parameters has become an important role in the neuroimaging, neurosurgical, and neurological community as a method to identify major white matter tracts afflicted by pathology or tracts at risk for a given surgical approach. We introduce a novel framework for a reliable and robust quantification of DTI parameters, which overcomes problems of existing techniques introduced by necessary user inputs. In a first step, a hybrid clustering method is proposed that allows for extracting specific fiber bundles in a robust way. Compared to previous methods, our approach considers only local proximities of fibers and is insensitive to their global geometry. This is very useful in cases where a fiber tracking of the whole brain is not available. Our technique determines the overall number of clusters iteratively using a eigenvalue thresholding technique to detect disjoint clusters of independent fiber bundles. Afterwards, possible finer substructures based on an eigenvalue regression are determined within each bundle. In a second step, a quantification of DTI parameters of the extracted bundle is performed. We propose a method that automatically determines a 3D image where the voxel values encode the minimum distance to a reconstructed fiber. This image allows for calculating a 3D mask where each voxel within the mask corresponds to a voxel that lies in an isosurface around the fibers. The mask is used for an automatic classification between tissue classes (fiber, background, and partial volume) so that the quantification can be performed on one or more of such classes. This can be done per slice or a single DTI parameter can be determined for the whole volume which is covered by the isosurface. Our experimental tests confirm that major white matter fiber tracts may be robustly determined and can be quantified automatically. A great advantage of our framework is its easy integration into existing quantification applications so that uncertainties can be reduced, and higher intrarater- as well as interrater reliabilities can be achieved.

Proceedings Article | 13 March 2008 Paper

Rapid prototyping of clinical software assistants

Jan Rexilius, Heinz-Otto Peitgen

Proceedings Volume 6919, 69190S (2008) https://doi.org/10.1117/12.771119

KEYWORDS: Software development, Algorithm development, Human-machine interfaces, Visualization, Image processing, Prototyping, Image visualization, Medical imaging, Rapid manufacturing, Clinical research

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Proceedings Article | 11 March 2008 Paper

A software assistant for the design of realistic software phantoms

Jan Rexilius, Olaf Konrad, Heinz-Otto Peitgen

Proceedings Volume 6914, 69144Y (2008) https://doi.org/10.1117/12.771608

KEYWORDS: Brain, Software development, Human-machine interfaces, Image segmentation, Medical imaging, Databases, Image analysis, Liver, Lung, Standards development

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Proceedings Article | 11 March 2008 Paper

Evaluation of accuracy in partial volume analysis of small objects

Jan Rexilius, Heinz-Otto Peitgen

Proceedings Volume 6914, 69144X (2008) https://doi.org/10.1117/12.771125

KEYWORDS: Photovoltaics, Tissues, Data modeling, Medical imaging, Avalanche photodetectors, Image classification, Magnetic resonance imaging, Expectation maximization algorithms, Image analysis, Statistical analysis

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Proceedings Article | 29 March 2007 Paper

Multispectral brain tumor segmentation based on histogram model adaptation

Jan Rexilius, Horst Hahn, Jan Klein, Markus Lentschig, Heinz-Otto Peitgen

Proceedings Volume 6514, 65140V (2007) https://doi.org/10.1117/12.709410

KEYWORDS: Tumors, Image segmentation, Brain, Tissues, Data modeling, Image registration, Neuroimaging, Magnetic resonance imaging, Skull, Motion models

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Proceedings Article | 21 March 2007 Paper

Grid-based spectral fiber clustering

Jan Klein, Philip Bittihn, Peter Ledochowitsch, Horst Hahn, Olaf Konrad, Jan Rexilius, Heinz-Otto Peitgen

Proceedings Volume 6509, 65091E (2007) https://doi.org/10.1117/12.706242

KEYWORDS: Detection and tracking algorithms, Structured optical fibers, Diffusion, Diffusion tensor imaging, Image segmentation, Image processing algorithms and systems, Visualization, Algorithm development, Medical imaging, 3D image reconstruction

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Proceedings Article | 13 March 2006 Paper

Embedding VTK and ITK into a visual programming and rapid prototyping platform

Matthias Koenig, Wolf Spindler, Jan Rexilius, Julien Jomier, Florian Link, Heinz-Otto Peitgen

Proceedings Volume 6141, 61412O (2006) https://doi.org/10.1117/12.652102

KEYWORDS: Visualization, Image processing, Computer programming, Image visualization, Human-machine interfaces, Medical imaging, Rapid manufacturing, C++, Image segmentation, Algorithm development

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Proceedings Article | 14 April 2005 Paper

White matter lesion phantom for diffusion tensor data and its application to the assessment of fiber tracking

Mathias Schluter, Olaf Konrad-Verse, Horst Hahn, Bram Stieltjes, Jan Rexilius, Heinz-Otto Peitgen

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.596197

KEYWORDS: Fourier transforms, Reconstruction algorithms, Diffusion, Diffusion tensor imaging, Tumors, Brain, Anisotropy, Detection and tracking algorithms, Computer simulations, Visualization

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Showing 5 of 9 publications

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