Automatic Insall-Salvati ratio measurement on lateral knee x-ray images using model-guided landmark localization

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

研究成果: Article

6 引文 (Scopus)

摘要

The Insall-Salvati ratio (ISR) is important for detecting two common clinical signs of knee disease: patella alta and patella baja. Furthermore, large interoperator differences in ISR measurement make an objective measurement system necessary for better clinical evaluation. In this paper, we define three specific bony landmarks for determining the ISR and then propose an x-ray image analysis system to localize these landmarks and measure the ISR. Due to inherent artifacts in x-ray images, such as unevenly distributed intensities, which make landmark localization difficult, we hence propose a registrationassisted active-shape model (RAASM) to localize these landmarks. We first construct a statistical model from a set of training images based on x-ray image intensity and patella shape. Since a knee x-ray image contains specific anatomical structures, we then design an algorithm, based on edge tracing, for patella feature extraction in order to automatically align the model to the patella image. We can estimate the landmark locations as well as the ISR after registration-assisted model fitting. Our proposed method successfully overcomes drawbacks caused by x-ray image artifacts. Experimental results show great agreement between the ISRs measured by the proposed method and by orthopedic clinicians.

原文English
頁(從 - 到)6785-6800
頁數16
期刊Physics in Medicine and Biology
55
發行號22
DOIs
出版狀態Published - 2010 十一月 21

指紋

Patella
Knee
X-Rays
Artifacts
Statistical Models
Orthopedics

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

引用此文

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abstract = "The Insall-Salvati ratio (ISR) is important for detecting two common clinical signs of knee disease: patella alta and patella baja. Furthermore, large interoperator differences in ISR measurement make an objective measurement system necessary for better clinical evaluation. In this paper, we define three specific bony landmarks for determining the ISR and then propose an x-ray image analysis system to localize these landmarks and measure the ISR. Due to inherent artifacts in x-ray images, such as unevenly distributed intensities, which make landmark localization difficult, we hence propose a registrationassisted active-shape model (RAASM) to localize these landmarks. We first construct a statistical model from a set of training images based on x-ray image intensity and patella shape. Since a knee x-ray image contains specific anatomical structures, we then design an algorithm, based on edge tracing, for patella feature extraction in order to automatically align the model to the patella image. We can estimate the landmark locations as well as the ISR after registration-assisted model fitting. Our proposed method successfully overcomes drawbacks caused by x-ray image artifacts. Experimental results show great agreement between the ISRs measured by the proposed method and by orthopedic clinicians.",
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AU - Sun, Yung-Nien

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