A joint-constraint model-based system for reconstructing total knee motion

Hsin Chen Chen, Chia Hsing Wu, Chien-Kuo Wang, Chii-Jeng Lin, Yung-Nien Sun

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Comprehending knee motion is an essential requirement for studying the causes of knee disorders. In this paper, we propose a new 2-D-3-D registration system based on joint-constraint model for reconstructing total knee motion. The proposed model that contains bone geometries and an articulated joint mechanism is first constructed from multipostural magnetic resonancevolumetric images. Then, the bone segments of the model are hierarchically registered to each frame of the given single-plane fluoroscopic video that records the knee activity. The bone posture is iteratively optimized using a modified chamfer matching algorithm to yield the simulated radiograph which is the best fit to the underlying fluoroscopic image. Unlike conventional registration methods computing posture parameters for each bone independently, the proposed femorotibial and patellofemoral joint models properly maintain the articulations between femur, tibia, and patella during the registration processes. As a result, we can obtain a sequence of registered knee postures showing smooth and reasonable physiologic patterns of motion. The proposed system also provides joint-space interpolation to densely generate intermediate postures for motion animation. The effectiveness of the proposed method was validated by computer simulation, animal cadaver, and in vivo knee testing. The mean target registration errors for femur, tibia, and patella were less than 1.5 mm. In particular, small out-of-plane registration errors [less than 1 mm (translation) and 2° (rotation)] were achieved in animal cadaver assessments.

Original languageEnglish
Article number6581861
Pages (from-to)171-181
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Volume61
Issue number1
DOIs
Publication statusPublished - 2014 Jan 1

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Bone
Animals
Animation
Interpolation
Geometry
Computer simulation
Testing

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

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abstract = "Comprehending knee motion is an essential requirement for studying the causes of knee disorders. In this paper, we propose a new 2-D-3-D registration system based on joint-constraint model for reconstructing total knee motion. The proposed model that contains bone geometries and an articulated joint mechanism is first constructed from multipostural magnetic resonancevolumetric images. Then, the bone segments of the model are hierarchically registered to each frame of the given single-plane fluoroscopic video that records the knee activity. The bone posture is iteratively optimized using a modified chamfer matching algorithm to yield the simulated radiograph which is the best fit to the underlying fluoroscopic image. Unlike conventional registration methods computing posture parameters for each bone independently, the proposed femorotibial and patellofemoral joint models properly maintain the articulations between femur, tibia, and patella during the registration processes. As a result, we can obtain a sequence of registered knee postures showing smooth and reasonable physiologic patterns of motion. The proposed system also provides joint-space interpolation to densely generate intermediate postures for motion animation. The effectiveness of the proposed method was validated by computer simulation, animal cadaver, and in vivo knee testing. The mean target registration errors for femur, tibia, and patella were less than 1.5 mm. In particular, small out-of-plane registration errors [less than 1 mm (translation) and 2° (rotation)] were achieved in animal cadaver assessments.",
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A joint-constraint model-based system for reconstructing total knee motion. / Chen, Hsin Chen; Wu, Chia Hsing; Wang, Chien-Kuo; Lin, Chii-Jeng; Sun, Yung-Nien.

In: IEEE Transactions on Biomedical Engineering, Vol. 61, No. 1, 6581861, 01.01.2014, p. 171-181.

Research output: Contribution to journalArticle

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