Automatic model-based roentgen stereophotogrammetric analysis (RSA) of total knee prostheses

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題名:	Automatic model-based roentgen stereophotogrammetric analysis (RSA) of total knee prostheses
作者:	賴景義;Syu, Ci-Bin;Lai, Jiing-Yih;Chang, Ren-Yi;Shih, Kao-Shang;Chen, Kuo-Jen;Lin, Shang-Chih
貢獻者:	工學院機械工程學系
關鍵詞:	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
日期:	2012-01-03
上傳時間:	2026-04-23 14:46:33 (UTC+8)
出版者:	Elsevier Ltd.;Kidlington: Elsevier Ltd
摘要:	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
顯示於類別:	[機械工程學系] 期刊論文

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