Information

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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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 9-11/186, 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/",
}