TY - GEN
T1 - Segmentation of the cartilage in the rib cage in 3D MRI
AU - Noorda, Y.H.
AU - Bartels, L.W.
AU - Pluim, J.P.W.
PY - 2012
Y1 - 2012
N2 - 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. © 2012 Springer-Verlag.
AB - 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. © 2012 Springer-Verlag.
U2 - 10.1007/978-3-642-33612-6_24
DO - 10.1007/978-3-642-33612-6_24
M3 - Conference contribution
SN - 978-3-642-33612-6
T3 - Lecture Notes in Computer Science
SP - 229
EP - 237
BT - 4th International Workshop on Computational and Clinical Applications in Abdominal Imaging
A2 - Yoshida, H.
A2 - Hawkes, D.
A2 - Vannier, M.W.
PB - Springer
CY - Berlin
T2 - 4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, October 1, 2012, Nice, France
Y2 - 1 October 2012 through 1 October 2012
ER -