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Enhancement and Visualization of VascularStructures in MRA Images Using Local Structure
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
2010 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

The novel method of this thesis work is based on using quadrature filters to estimate an orientation tensor and to use the advantage of tensor information to control 3D adaptive filters. The adaptive filters are applied to enhance the Magnetic Resonance Angiography (MRA) images. The tubular structures are extracted from the volume dataset by using the quadrature filters. The idea of developing adaptive filtering in this thesis work is to enhance the volume dataset and suppress the image noise. Then the output of the adaptive filtering can be a clean dataset for segmentation of blood vessel structures to get appropriate volume visualization.

The local tensors are used to create the control tensor which is used to control adaptive filters. By evaluation of the tensor eigenvalues combination, the local structures like tubular structures and stenosis structures are extracted from the dataset. The method has been evaluated with synthetic objects, which are vessel models (for segmentation), and onion like synthetic object (for enhancement). The experimental results are shown on clinical images to validate the proposed method as well.

Place, publisher, year, edition, pages
2010. , 64 p.
Keyword [en]
Adaptive Filtering, Tubular Structure, 3D Filter, Enhancement, Local Structure
National Category
Natural Sciences
URN: urn:nbn:se:liu:diva-57472ISRN: LiTH-IMT/MASTER-EX--10/003--SEOAI: diva2:325802
Subject / course
Masterprogram Biomedical Engineering (BME)
2010-06-16, 20:06 (English)
Available from: 2010-06-29 Created: 2010-06-20 Last updated: 2012-06-12Bibliographically approved

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Medical InformaticsThe Institute of Technology
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ReferencesLink to record
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