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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/108392


    Title: Automatic model-based roentgen stereophotogrammetric analysis (RSA) of total knee prostheses
    Authors: 賴景義;Syu, Ci-Bin;Lai, Jiing-Yih;Chang, Ren-Yi;Shih, Kao-Shang;Chen, Kuo-Jen;Lin, Shang-Chih
    Contributors: 工學院機械工程學系
    Keywords: Algorithms;Arthroplasty, Replacement, Knee - methods;Automation;Biological and medical sciences;Biomedical materials;Computer Simulation;Computerized, statistical medical data processing and models in biomedicine;Efficiency;Errors;Humans;Knee;Knee Joint - diagnostic imaging;Knee Joint - surgery;Knee Prosthesis;Mathematical models;Medical management aid. Diagnosis aid;Medical sciences;Methods;Models, Anatomic;Models, Biological;Orthopedic surgery;Personal relationships;Physical Medicine and Rehabilitation;Prostheses;Prosthesis;Prosthetics;Radiographic Image Interpretation, Computer-Assisted - methods;Radiostereometric Analysis - methods;Registration;Roentgen;RSA;Studies;Surgery (general aspects). Transplantations, organ and tissue grafts. Graft diseases;Surgical implants
    Date: 2012-01-03
    Issue Date: 2026-04-23 14:46:33 (UTC+8)
    Publisher: Elsevier Ltd.;Kidlington: Elsevier Ltd
    Abstract: 摘要: Conventional radiography is insensitive for early and accurate estimation of the mal-alignment and wear of knee prostheses. The two-staged (rough and fine) registration of the model-based RSA technique has recently been developed to in vivo estimate the prosthetic pose (i.e, location and orientation). In the literature, rough registration often uses template match or manual adjustment of the roentgen images. Additionally, possible error induced by the nonorthogonality of taking two roentgen images neither examined nor calibrated prior to fine registration. This study developed two RSA methods for automate the estimation of the prosthetic pose and decrease the nonorthogonality-induced error. The predicted results were validated by both simulative and experimental tests and compared with reported findings in the literature. The outcome revealed that the feature-recognized method automates pose estimation and significantly increases the execution efficiency up to about 50 times in comparison with the literature counterparts. Although the nonorthogonal images resulted in undesirable errors, the outline-optimized method can effectively compensate for the induced errors prior to fine registration. The superiority in automation, efficiency, and accuracy demonstrated the clinical practicability of the two proposed methods especially for the numerous fluoroscopic images of dynamic motion.
    其他題名: J Biomech
    出版者: Kidlington: Elsevier Ltd
    出版日期: 2012-01-03
    出處: Journal of biomechanics, 2012-01, Vol.45 (1), p.164-171
    版權: 2011 Elsevier Ltd
    版權: Elsevier Ltd
    版權: 2015 INIST-CNRS
    版權: Copyright © 2011 Elsevier Ltd. All rights reserved.
    識別號: ISSN: 0021-9290
    識別號: ISSN: 1873-2380
    識別號: EISSN: 1873-2380
    識別號: DOI: 10.1016/j.jbiomech.2011.09.011
    識別號: PMID: 22093794
    Appears in Collections:[Departmant of Mechanical Engineering ] journal & Dissertation

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