title: Improve accuracy for automatic acetabulum segmentation in CT images.
abstract: Separation of the femur head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. To improve the segmentation accuracy is the key point of existing automatic or semi-automatic segmentation methods. In this paper, we propose a new method to improve the accuracy of the segmented acetabulum using surface fitting techniques, which essentially consists of three parts: (1) design a surface iterative process to obtain an optimization surface; (2) change the ellipsoid fitting to two-phase quadric surface fitting; (3) bring in a normal matching method and an optimization region method to capture edge points for the fitting quadric surface. Furthermore, this paper cited vivo CT data sets of 40 actual patients (with 79 hip joints). Test results for these clinical cases show that: (1) the average error of the quadric surface fitting method is 2.3 (mm); (2) the accuracy ratio of automatically recognized contours is larger than 89.4%; (3) the error ratio of section contours is less than 10% for acetabulums without severe malformation and less than 30% for acetabulums with severe malformation. Compared with similar methods, the accuracy of our method, which is applied in a software system, is significantly enhanced.
authors.affiliation: Nanjing University of Aeronautics and Astronautics, P.R. China Jinling Hospital, Department Orthopedics, Nanjing University School of Medicine, P.R. China.
authors.forename: Hao
authors.initials: H
authors.lastname: Liu
authors.affiliation: Jinling Hospital, Department Orthopedics, Nanjing University School of Medicine, P.R. China.
authors.forename: Jianning
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Nanjing University of Aeronautics and Astronautics, P.R. China.
authors.forename: Ning
authors.initials: N
authors.lastname: Dai
authors.affiliation: Jinling Hospital, Department Orthopedics, Nanjing University School of Medicine, P.R. China.
authors.forename: Hongbo
authors.initials: H
authors.lastname: Qian
authors.affiliation: Nanjing University of Aeronautics and Astronautics, P.R. China.
authors.forename: Yuehong
authors.initials: Y
authors.lastname: Tang
mesh_terms: D000077:Acetabulum / Q000000981:diagnostic imaging*; D000465:Algorithms; D001185:Artificial Intelligence; D006621:Hip Joint / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007592:Joint Diseases / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Acetabulum; computer tomography; edge points; ellipsoid fitting; segmentation