Abstract
Interventional non-invasive MR-guided techniques for treatment of liver tumors, such as HIFU, could benefit greatly from automatic cartilage detection. In this paper, segmentation of the cartilage in the rib cage is performed in 3D MR images. This is a challenging task, due to the poor contrast between cartilage and muscle, and the non-uniform intensity of the cartilage.
Our segmentation algorithm is based on feature selection by analyzing orientation and vesselness, automatic sternum localization using anatomical knowledge, skeletonization and ridge finding, and level set evolution.
We show that our algorithm is capable of detecting all visible cartilage structures in the scans. Gaps and false positives may occur, due to lack of contrast or the presence of non-cartilage structures with similar features. However, the segmentation is accurate, even for regions with low contrast, with an average error of the boundary of 1.1 mm.
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Noorda, Y.H., Bartels, L.W., Pluim, J.P.W. (2012). Segmentation of the Cartilage in the Rib Cage in 3D MRI. In: Yoshida, H., Hawkes, D., Vannier, M.W. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2012. Lecture Notes in Computer Science, vol 7601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33612-6_24
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DOI: https://doi.org/10.1007/978-3-642-33612-6_24
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