Abstract
Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we present a novel and fast 3D segmentation framework of VBs in clinical CT images using the graph cuts method. The Matched filter is employed to detect the VB region automatically. In the graph cuts method, a VB (object) and surrounding organs (background) are represented using a gray level distribution models which are approximated by a linear combination of Gaussians (LCG) to better specify region borders between two classes (object and background). Initial segmentation based on the LCG models is then iteratively refined by using MGRF with analytically estimated potentials. In this step, the graph cuts is used as a global optimization algorithm to find the segmented data that minimize a certain energy function, which integrates the LCG model and the MGRF model. Validity was analyzed using ground truths of data sets (expert segmentation) and the European Spine Phantom (ESP) as a known reference. Experiments on the data sets show that the proposed segmentation approach is more accurate than other known alternatives.
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Aslan, M.S. et al. (2009). A Novel 3D Segmentation of Vertebral Bones from Volumetric CT Images Using Graph Cuts. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_49
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DOI: https://doi.org/10.1007/978-3-642-10520-3_49
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