Information
- Publication Type: Master Thesis
- Workgroup(s)/Project(s):
- Date: April 2015
- First Supervisor: Eduard Gröller
Abstract
This thesis presents a novel method for the visual quantification of cerebral arteries. The Circle of Willis (CoW) is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle can lead to strokes. The diagnosis of stroke patients is complex and relies on the radiologist’s expertise and the software tools used. These tools consist of very basic display methods of the volumetric data without support of state-of-the-art technologies in medical image processing and visualization. The goal of this thesis is to create an automated method for the standardized visualization of cerebral arteries in stroke patients in order to allow visual indications of problematic areas as well as straightforward inter-patient comparisons.Prior to the visualization, this work offers a solution for the extraction of the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images. An enumeration technique for the labeling of the segments is therefore suggested. Furthermore, it proposes a method for the detection of the CoW’s main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the volume. This work gives a comprehensive account of the entire pipeline that is required to extract the arteries in the CoW and to build a model for the standardized visualization. The final goal of this thesis is to create an effective display of the arteries based on a radial tree layout.
The feasibility of the visual quantification method is tested in a study of 63 TOF-MRAs. With the proposed methodology applied to the subjects, the results were compared to the findings from radiologists. The obtained results demonstrate that the proposed techniques are effective in detecting the arteries of the CoW. Finally, we focused our methods on the identification of the main arteries.
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No further information available.BibTeX
@mastersthesis{Miao_Haichao_2015_VQC, title = "Visual Quantification of the Circle of Willis in Stroke Patients", author = "Haichao Miao", year = "2015", abstract = "This thesis presents a novel method for the visual quantification of cerebral arteries. The Circle of Willis (CoW) is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle can lead to strokes. The diagnosis of stroke patients is complex and relies on the radiologist’s expertise and the software tools used. These tools consist of very basic display methods of the volumetric data without support of state-of-the-art technologies in medical image processing and visualization. The goal of this thesis is to create an automated method for the standardized visualization of cerebral arteries in stroke patients in order to allow visual indications of problematic areas as well as straightforward inter-patient comparisons. Prior to the visualization, this work offers a solution for the extraction of the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images. An enumeration technique for the labeling of the segments is therefore suggested. Furthermore, it proposes a method for the detection of the CoW’s main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the volume. This work gives a comprehensive account of the entire pipeline that is required to extract the arteries in the CoW and to build a model for the standardized visualization. The final goal of this thesis is to create an effective display of the arteries based on a radial tree layout. The feasibility of the visual quantification method is tested in a study of 63 TOF-MRAs. With the proposed methodology applied to the subjects, the results were compared to the findings from radiologists. The obtained results demonstrate that the proposed techniques are effective in detecting the arteries of the CoW. Finally, we focused our methods on the identification of the main arteries.", month = apr, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", URL = "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/", }