Abstract
Many anatomical entities like different parts of the arterial system and the airway system are of tree-like structure. State of the art medical imaging systems can acquire 3D volume data of the human body at a resolution that is sufficient for the visualization of these tree structures. We present a general framework for the simultaneous segmentation and reconstruction of the abovementioned entities and apply it to the extraction of coronary arteries from multi detector-row CT data. The coronary artery extraction is evaluated on 9 data-sets with known ground truth for the centerlines of the coronary arteries.
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Bülow, T., Lorenz, C., Renisch, S. (2004). A General Framework for Tree Segmentation and Reconstruction from Medical Volume Data. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_65
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DOI: https://doi.org/10.1007/978-3-540-30135-6_65
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