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Abstract

Coronary artery diseases are among the leading causes of death in the industrial countries. The high death rate leads to an increased demand of diagnosis and treatment of these diseases. Additional to the conventional coronary angiography, the CT angiography is mainly used in the extended diagnostics of coronary artery diseases. This modality allows a detailed assessment of the coronary vessels and potentially present stenoses. For supporting the radiologist during the evaluation of the coronary arteries by the help of computer-aided diagnostic methods, robust and ecient procedures for the tracking of coronary arteries are needed. The approach presented in this thesis uni es the strong points of existing methods delivering high accuracy with the strong points of methods achieving high overlap. Therefore the approach presented in this thesis aims at highly accurate results in combination with high overlap of the investigated coronary artery vessel tree. The approach is divided into three phases: 1) calculation of seed points, 2) tracking of vessel segments, and 3) construction of the coronary artery trees. Phase 1 & 2 are executed in an automatic manner. First potential seed points for the tracking of vessel segments are identi ed. During the second phase, vessel segments located at these seed points are tracked by use of a cylindrical shape model. By use of rule-based anatomical heuristics, the third and nal phase combines vessel segments to form complete coronary artery trees. This phase requires minimal user interaction, as the location of the root of the left and right coronary artery tree needs to be speci ed. Beside the detailed description of the algorithm, the integration into a professional radiology workstation is demonstrated. The results obtained by the evaluation on 24 CTA datasets show a high overlap (OV) of 89.5% in combination with very precise accuracy (AI) of 0.24 mm in comparison to an expert-annotated reference segmentation.

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BibTeX

@mastersthesis{Gruenauer-2011-CAT,
  title =      "Coronary Artery Tracking with Rule-based Gap Closing",
  author =     "Andreas Gr\"{u}nauer",
  year =       "2011",
  abstract =   "Coronary artery diseases are among the leading causes of
               death in the industrial countries. The high death rate leads
               to an increased demand of diagnosis and treatment of these
               diseases. Additional to the conventional coronary
               angiography, the CT angiography is mainly used in the
               extended diagnostics of coronary artery diseases. This
               modality allows a detailed assessment of the coronary
               vessels and potentially present stenoses. For supporting the
               radiologist during the evaluation of the coronary arteries
               by the help of computer-aided diagnostic methods, robust and
               ecient procedures for the tracking of coronary arteries are
               needed. The approach presented in this thesis unies the
               strong points of existing methods delivering high accuracy
               with the strong points of methods achieving high overlap.
               Therefore the approach presented in this thesis aims at
               highly accurate results in combination with high overlap of
               the investigated coronary artery vessel tree. The approach
               is divided into three phases: 1) calculation of seed points,
               2) tracking of vessel segments, and 3) construction of the
               coronary artery trees. Phase 1 & 2 are executed in an
               automatic manner. First potential seed points for the
               tracking of vessel segments are identied. During the second
               phase, vessel segments located at these seed points are
               tracked by use of a cylindrical shape model. By use of
               rule-based anatomical heuristics, the third and nal phase
               combines vessel segments to form complete coronary artery
               trees. This phase requires minimal user interaction, as the
               location of the root of the left and right coronary artery
               tree needs to be specied. Beside the detailed description
               of the algorithm, the integration into a professional
               radiology workstation is demonstrated. The results obtained
               by the evaluation on 24 CTA datasets show a high overlap
               (OV) of 89.5% in combination with very precise accuracy (AI)
               of 0.24 mm in comparison to an expert-annotated reference
               segmentation.",
  month =      jul,
  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/2011/Gruenauer-2011-CAT/",
}