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Automated Joint Space Detection Improves Bone Segmentation Accuracy
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An automatic bone segmentation method based on anatomical structure for the knee joint in MDCT image

Y Uozumi, K Nagamune

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
    PubMed

    Abstract:

    The purpose of this study is to propose an automatic segmentation about each bone (the femur, the tibia, the patellar, and fibular) of the knee in MDCT image. The proposed method was applied for six patients (Age 33 ± 13, four males/tew females). The proposed method segmented the knee joint into each bone by using anatomical structure for the knee joint. The experiments calculate matching rate of the manual and the proposed method for evaluating it. As a result, The matching rate of the femur, the tibia, the patellar, and fibula were 95.84 ± 0.57%, 94.12 ± 1.01%, 94.49 ± 0.83%, 86.37 ± 4.28%, respectively. This study concluded that the proposed method is enough to segment the knee bones.

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