The extraction and analysis of the aortic arch in chest computed tomography (CT) data can be an important preliminary step for the diagnosis and treatment planning of e.g.~ lung cancer. We here present a new method for automatic aortic arch extraction and detection of the main arterial branchings that may serve as segmentation seeds or as landmarks for intra- and interpatient registration of the mediastinum. Our method, which is based on Hough and Euclidean distance transforms and probability weighting, works on both contrast enhanced and non-contrast CT. A comparison to data manually extracted from 40 cases shows its robustness at an acceptable overall runtime.     «

The extraction and analysis of the aortic arch in chest computed tomography (CT) data can be an important preliminary step for the diagnosis and treatment planning of e.g.~ lung cancer. We here present a new method for automatic aortic arch extraction and detection of the main arterial branchings that may serve as segmentation seeds or as landmarks for intra- and interpatient registration of the mediastinum. Our method, which is based on Hough and Euclidean distance transforms and probability we...     »