12 March 2018 MRI-based active shape model of the human proximal femur using fiducial and secondary landmarks and its validation
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Osteoporosis, associated with reduced bone mineral density and structural degeneration, greatly increases the risk of fragility fracture. A major challenge of volumetric bone imaging of the hip is the selection of regions of interest (ROIs) for computation of regional bone measurements. Here, we develop an MRI-based active shape model (ASM) of the human proximal femur used to automatically generate ROIs. Major challenges in developing the ASM of a complex three-dimensional (3-D) shape lie in determining a large number of anatomically consistent landmarks for a set of training shapes. In this paper, we develop a new method of generating the proximal femur ASM, where two types of landmarks, namely fiducial and secondary landmarks, are used. The method of computing the MRI-based proximal femur ASM consists of—(1) segmentation of the proximal femur bone volume, (2) smoothing the bone surface, (3) drawing fiducial landmark lines on training shapes, (4) drawing secondary landmarks on a reference shape, (5) landmark mesh generation on the reference shape using both fiducial and secondary landmarks, (6) generation of secondary landmarks on other training shapes using the correspondence of fiducial landmarks and an elastic deformation of the landmark mesh, (7) computation of the active shape model. An MRI-based shape model of the human proximalfemur has been developed using hip MR scans of 45 post-menopausal women. The results of secondary landmark generation were visually satisfactory and no topology violation or notable geometric distortion artifacts were observed. Performance of the method was examined in terms of shape representation errors in a leave-one-out test. The mean and standard deviation of leave-one-out shape representation errors were 2.27 and 0.61 voxels respectively. The experimental results suggest that the framework of fiducial and secondary landmark allows reliable computation statistical shape models for complex 3-D anatomic structures.
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Xiaoliu Zhang, Xiaoliu Zhang, Cheng Chen, Cheng Chen, Sean Boone, Sean Boone, Vivek Joshi, Vivek Joshi, Arakua Welbeck, Arakua Welbeck, Guoyuan Liang, Guoyuan Liang, Gregory Chang, Gregory Chang, Punam K. Saha, Punam K. Saha, } "MRI-based active shape model of the human proximal femur using fiducial and secondary landmarks and its validation ", Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 105781L (12 March 2018); doi: 10.1117/12.2293732; https://doi.org/10.1117/12.2293732

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