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Fast detection modelling of the real osteoarthritic holes in the human knee with contour interpolated radial basis functions

机译:用轮廓插入径向基函数的人体膝关节中真正骨关节炎孔的快速检测与建模

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In this article, we propose a novel method for the fast 3D reconstruction of real osteoarthritic (OA) holes in a human femoral cartilage. Initially, semi-automated Region-Based Segmentation (region-growing) and Bounding Box techniques are used to extract femoral cartilage slices from MRI scans of the knee. OA holes were detected and filled automatically by our contour interpolation/RBF (CI-RBF) method and 3D models of both the femoral cartilage and OA holes were reconstructed separately. The method was then applied to a single human knee and results proved it fast, reliable and accurate for reconstructing a 3D model of the femoral cartilage from MRI images with an extremely low root mean square error of 1.67% in the estimated volume of the automatically filled to the manually filled femoral cartilage slices. As per authors' knowledge this is the first time real OA hole has automatically been identified and filled.
机译:在本文中,我们提出了一种新的方法,用于人类股骨软骨中真正的骨关节炎(OA)孔的快速三维重建。 最初,基于半自动区域的分割(区域 - 成长)和边界盒技术用于从膝盖的MRI扫描中提取股骨软骨切片。 通过我们的轮廓插值/ RBF(CI-RBF)方法自动检测和填充OA孔,分别重建股骨软骨和OA孔的3D模型。 然后将该方法施用于单个人膝盖,并证明了从MRI图像重建股骨软骨的3D模型的快速,可靠,准确,在估计的自动填充的估计体积中为1.67%的极低均方误差为1.67% 到手动填充的股骨软骨切片。 根据作者的知识,这是第一次真正的OA孔自动识别和填充。

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