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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 呂東武 | zh_TW |
| dc.contributor.advisor | Tung-Wu Lu | en |
| dc.contributor.author | 吳冠賢 | zh_TW |
| dc.contributor.author | Kuan-Hsien Wu | en |
| dc.date.accessioned | 2021-07-11T15:08:11Z | - |
| dc.date.available | 2024-08-15 | - |
| dc.date.copyright | 2019-08-23 | - |
| dc.date.issued | 2019 | - |
| dc.date.submitted | 2002-01-01 | - |
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Taylor, Statistical models of appearance for computer vision. 2004, Technical report, University of Manchester. 41. Goodall, C., Procrustes Methods in the Statistical-Analysis of Shape. Journal of the Royal Statistical Society Series B-Methodological, 1991. 53(2): p. 285-339. 42. Wold, S., K. Esbensen, and P. Geladi, Principal Component Analysis. Chemometrics and Intelligent Laboratory Systems, 1987. 2(1-3): p. 37-52. 43. Heimann, T. and H.P. Meinzer, Statistical shape models for 3D medical image segmentation: A review. Medical Image Analysis, 2009. 13(4): p. 543-563. 44. Baltzopoulos, V., A videofluoroscopy method for optical distortion correction and measurement of knee-joint kinematics. Clinical Biomechanics, 1995. 10(2): p. 85-92. 45. Lin, C.C., et al., A model-based tracking method for measuring 3D dynamic joint motion using an alternating biplane x-ray imaging system. Med Phys, 2018. 46. Kaptein, B.L., et al., A comparison of calibration methods for stereo fluoroscopic imaging systems. J Biomech, 2011. 44(13): p. 2511-5. 47. Hatze, H., High-precision three-dimensional photogrammetric calibration and object space reconstruction using a modified DLT-approach. J Biomech, 1988. 21(7): p. 533-8. 48. Siddon, R.L., Fast calculation of the exact radiological path for a three-dimensional CT array. Med Phys, 1985. 12(2): p. 252-5. 49. Goldberg, D.E. and J.H. Holland, Genetic algorithms and machine learning. Machine learning, 1988. 3(2): p. 95-99. 50. Penney, G.P., et al., A comparison of similarity measures for use in 2-D-3-D medical image registration. IEEE transactions on medical imaging, 1998. 17(4): p. 586-595. 51. Miranda, D.L., et al., Automatic determination of anatomical coordinate systems for three-dimensional bone models of the isolated human knee. J Biomech, 2010. 43(8): p. 1623-6. 52. Wu, G. and P.R. Cavanagh, ISB recommendations for standardization in the reporting of kinematic data. J Biomech, 1995. 28(10): p. 1257-61. 53. Cignoni, P., C. Rocchini, and R. Scopigno, Metro: Measuring error on simplified surfaces. Computer Graphics Forum, 1998. 17(2): p. 167-174. 54. Yue, B., et al., Differences of knee anthropometry between Chinese and white men and women. J Arthroplasty, 2011. 26(1): p. 124-30. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78626 | - |
| dc.description.abstract | 基於雙平面動態X光影像進行比對得到運動學資訊,並結合核磁共振掃描所得之三維軟骨模型求得膝關節面運動學,在目前為活體非侵入性方法中較精確且常見的,而在量測膝關節面運動學中,重建個人化三維軟骨模型是最為重要的,然而目前最精確的方法是透過核磁共振掃描影像進行重建,其會有花費過高、時間因素以及核磁共振骨頭模型精度不佳等問題,並且在後續分析上也會遇到兩種不同來源的模型因影像解析度等因素使得外形有誤差。因此後來便有許多研究致力於發展僅透過電腦斷層掃瞄資訊即可計算關節面接觸運動學的方法,過去本實驗室有提出的平均厚度虛擬軟骨方法,然而其誤差普遍偏高,能否能達到膝關節面運動學之精度需求是很值得探討的。因此本研究之目的即為提出一個基於統計形狀模型的方法,能夠透過電腦斷層掃描之膝關節骨模型等資訊,計算其膝關節面運動學資訊。
本研究以三十五隻膝關節軟骨模型建立膝關節軟骨形狀統計模型,並開發搭配受試者進行彎曲伸直時的運動學資訊,重建出用以計算膝關節運動學之個人化膝關節軟骨模型,並透過活體實驗,以驗證此方法之可行性,並量化三維軟骨模型重建誤差以及其應用於膝關節面運動學計算結果誤差。 本研究的結果顯示,用於計算膝關節面運動學的模型重建上,在內側膝關節所得之接觸點誤差依前後方向、近遠端方向和內外側方向分別為1.33±0.71mm、1.23±0.50mm以及2.64±1.48mm,在外側膝關節所得之接觸點誤差分別為0.77±0.37mm、1.01±0.87mm以及2.26±1.48mm。本研究所開發之方法相較於以前之均勻厚度虛擬軟骨計算法要來的精準,具有足夠應用於膝關節面運動學的計算。 | zh_TW |
| dc.description.abstract | Measuring knee joint arthrokinematics by using bi-plane fluoroscopic image and magnetic resonance imaging cartilage model is a common and accurate in-vivo non-invasive method. The most important part of this method is the subject-specific cartilage model reconstruction. Currently, the most accurate cartilage models are reconstructed by the magnetic resonance images (MRI). However, MRI may cause some concerns such as expensive, and the poor accuracy of the MRI bone model. Therefore, many studies have been devoted to the development of methods for calculating arthrokinematics by only CT bone information. Our lab has proposed the average thickness virtual cartilage method of measuring knee joint arthrokinematics, but its error is generally high. Therefore, the purpose of this study is to propose a method based on statistical shape model, which can calculate the arthrokinematics of knee joint only through information such as knee joint kinematic and the CT bone model.
The study collects 35 models of cartilages of knee joint to establish the knee joint statistical shape model (SSM), and develop a method for reconstruction of subject-specific cartilages of knee joint (SSM-K) to measuring knee joint arthrokinematics while cycling via flexion-extension kinematic and the CT bone model. The in-vivo experiments were performed to verify the feasibility of this method, and to quantify the reconstruction error of the three-dimensional cartilage model and its arthrokinematics calculation error. The result showed the contact point error calculated on the medial side of the knee joint was 1.33±0.71mm on the anterior-posterior direction (AP), 1.23±0.50mm on the proximal-distal direction (DP), and 2.64±1.48mm on the medial-lateral direction (ML). On the other hand, the contact point error calculated on the lateral side of the knee joint was 0.77±0.37mm on the anterior-posterior direction (AP), 1.01±0.87mm on the proximal -distal direction (DP), and 1.01±0.87mm on the medial-lateral direction (ML). This indicated that the method developed in this study is more accurate than the previous uniform thickness virtual cartilage method, and has sufficient calculation for knee joint surface kinematics. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-11T15:08:11Z (GMT). No. of bitstreams: 1 ntu-108-R06548024-1.pdf: 3661690 bytes, checksum: 69428a2c42ec432453d8608f335f9a4a (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 摘要 I
Abstract II 圖目錄 V 表目錄 X 第一章 緒論 1 第一節 研究背景 1 第二節 膝關節之解剖學 2 第三節 膝關節之運動學 5 第四節 文獻回顧 6 第五節 研究目的 11 第二章 材料與方法 12 第一節 訓練模型 12 第二節 統計形狀模型 13 一、 模型相對應關係 (Shape Correspondence) 13 二、 建構模型變異 (Shape Variation) 14 第三節 活體膝關節運動學量測 16 一、 受試者 16 二、 儀器設備 17 三、 系統校正 19 四、 活體膝關節三維運動學資訊蒐集 23 第四節 統計模型參數最佳化 29 第五節 誤差之量化 30 一、 模型形狀誤差 30 二、 關節面運動學誤差 30 第三章 研究結果 31 第一節 統計形狀模型 31 第二節 統計形狀模型變形重建模型 34 一、 模型形狀誤差 34 二、 關節面運動學誤差 40 第四章 討論 53 第五章 結論 55 研究限制 55 未來展望 55 參考文獻 56 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 個人化軟骨模型重建 | zh_TW |
| dc.subject | 統計形狀模型 | zh_TW |
| dc.subject | 動態X光 | zh_TW |
| dc.subject | 核磁共振 | zh_TW |
| dc.subject | 電腦斷層掃描 | zh_TW |
| dc.subject | 膝關節 | zh_TW |
| dc.subject | 運動學 | zh_TW |
| dc.subject | 關節面運動學 | zh_TW |
| dc.subject | computed tomography | en |
| dc.subject | subject-specific cartilage model reconstruction | en |
| dc.subject | statistical shape model | en |
| dc.subject | fluoroscopy | en |
| dc.subject | magnetic resonance imaging | en |
| dc.subject | Arthrokinematics | en |
| dc.subject | kinematics | en |
| dc.subject | knee | en |
| dc.title | 發展人體膝關節軟骨形狀統計模型以利描述其關節面運動 | zh_TW |
| dc.title | Development of a Statistical Shape Model of the Human Knee Cartilage for the Description of the Surface Kinematics of the Knee | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 107-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 林正忠 | zh_TW |
| dc.contributor.coadvisor | Cheng-Chung Lin | en |
| dc.contributor.oralexamcommittee | 陳文斌;陳祥和 | zh_TW |
| dc.contributor.oralexamcommittee | Weng-Pin Chen;Hsiang-Ho Chen | en |
| dc.subject.keyword | 個人化軟骨模型重建,統計形狀模型,動態X光,核磁共振,電腦斷層掃描,膝關節,運動學,關節面運動學, | zh_TW |
| dc.subject.keyword | subject-specific cartilage model reconstruction,statistical shape model,fluoroscopy,magnetic resonance imaging,computed tomography,knee,kinematics,Arthrokinematics, | en |
| dc.relation.page | 58 | - |
| dc.identifier.doi | 10.6342/NTU201903318 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2019-08-13 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 醫學工程學系 | - |
| dc.date.embargo-lift | 2029-12-31 | - |
| Appears in Collections: | 醫學工程學研究所 | |
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| ntu-107-2.pdf Restricted Access | 3.58 MB | Adobe PDF |
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