title: Quantification of osteoarticular joint defects through bone segmentation and modeling.
abstract: Shoulder instability is a major threat to people's daily life. Many patients suffer from shoulder instability such as the loss of the glenoid and humeral head. In clinical practice, an accurate 3D structure estimation of damaged joints is necessary to diagnose and treat bone defects. This study quantifies osteoarticular defects through the modeling and visualization of osteoarticular structures. An improved algorithm to extract the 3D structure of the bones is proposed. The bone contour is then automatically extracted using prior shape and gray scale intensity distribution of joint CT images. Joint structures with mirror symmetry are matched using the Iterative Closest Point registration algorithm. Osteoarticular defects can be quantified on the basis of the symmetric information of the bones. Experimental results demonstrate that the proposed method can effectively segment the joint structures from the CT image. In addition, the proposed mirror symmetrical method can effectively estimate osteoarticular defects.
authors.affiliation: Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Tianyu
authors.initials: T
authors.lastname: Fu
authors.affiliation: Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Danni
authors.initials: D
authors.lastname: Ai
authors.affiliation: School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Huijun
authors.initials: H
authors.lastname: Xing
authors.affiliation: School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Qin
authors.initials: Q
authors.lastname: Li
authors.affiliation: Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing 100081, China.
authors.forename: Yongtian
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D007592:Joint Diseases / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D008954:Models, Biological; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012785:Shoulder Joint / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Joint bone; modeling; quantitative analysis; segmentation