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14 March 2011A framework for automated coronary artery tracking of low axial resolution multi slice CT images
Low axial resolution data such as multi-slice CT(MSCT) used for coronary artery disease screening
must balance the potential loss in image clarity, detail and partial volume effects with the benefits to the
patient such as faster acquisition time leading to lower dose exposure. In addition, tracking of the coronary
arteries can aid the location of objects contained within, thus helping to differentiate them from similar in
appearance, difficult to discern neighbouring regions.
A fully automated system has been developed to segment and track the main coronary arteries and
visualize the results. Automated heart isolation is carried out for each slice of an MSCT image using
active contour methods. Ascending aorta and artery root segmentation is performed using a combination of
active contours, morphological operators and geometric analysis of coronary anatomy to identify a starting
point for vessel tracking. Artery tracking and backtracking employs analysis of vessel position combined
with segmented region shape analysis to obtain artery paths. Robust, accurate threshold parameters are
calculated for segmentation utilizing Gaussian Mixture Model fitting and analysis.
The low axial resolution of our MSCT data sets, in combination with poor image clarity and noise
presented the greatest challenge. Classification techniques such as shape analysis have been utilized to
good effect and our results to date have shown that such deficiencies in the data can be overcome, further
promoting the positive benefits to patients.
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Jing Wu, Gordon Ferns M.D., John Giles M.D., Emma Lewis, "A framework for automated coronary artery tracking of low axial resolution multi slice CT images," Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796234 (14 March 2011); https://doi.org/10.1117/12.877963