| Summary: | 碩士 === 國立交通大學 === 生醫工程研究所 === 104 === Coronary arterial disease (CAD) is one of today's major causes of death. Although it is usually considered a disease for older people, put lifestyles of high-fat diets and lack of exercises have lowered the ages of people getting this disease. Given the progress of computed tomography techniques, this fast and non-intrusive technique has an important tool for detecting and diagnosing CAD. However, it takes specialized knowledge and is time-consuming to analyze the CT data. As a result, automatic coronary artery extraction techniques have become very useful.
One major approach for extracting coronary arteries is to first identify potential candidate points in the CT images, and then link them to form the coronary trees. If we can obtain very accurate candidate points, we can get very complete coronary arteries. In this thesis, our objective is to utilize the typical spatial positioning of coronary arteries within the heart, focusing on the two planes that typically contain the major coronary arteries. By detecting these planes first, we can filter the candidate points to remove noise points, reduce amount of computation, and lower the chances of false detections.
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