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    A signature dissimilarity measure for trabecular bone texture in knee radiographs

    Access Status
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    Authors
    Woloszynski, Tomasz
    Podsiadlo, Pawel
    Kurzynski, M.
    Stachowiak, Gwidon
    Date
    2010
    Type
    Journal Article
    
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    Citation
    Woloszynski, T. and Podsiadlo, P. and Stachowiak, G.W and Kurzynski, M. 2010. A signature dissimilarity measure for trabecular bone texture in knee radiographs. Medical Physics. 37 (5): pp. 2030-2042.
    Source Title
    Medical Physics
    DOI
    10.1118/1.3373522
    ISSN
    00942405
    URI
    http://hdl.handle.net/20.500.11937/23628
    Collection
    • Curtin Research Publications
    Abstract

    PURPOSE: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. METHODS: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size, anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP).RESULTS: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00 - x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (> 64 x 64 pixels). However, the measure is sensitive to changes in projection angle (> 5 degrees), image anisotropy (> 30 degrees), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%).CONCLUSIONS: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.

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    • A dissimilarity-based multiple classifier system for trabecular bone texture in detection and prediction of progression of knee osteoarthritis
      Woloszynski, Tomasz; Podsiadlo, Pawel; Stachowiak, Gwidon; Kurzynski, M. (2012)
      There is a growing need for classification systems that can accurately detect and predict knee osteoarthritis (OA) from plain radiographs. For this purpose, a system based on a support vector machine (SVM) classifier and ...
    • Prediction of progression of radiographic knee osteoarthritis using tibial trabecular bone texture
      Woloszynski, Tomasz; Podsiadlo, Pawel; Stachowiak, Gwidon; Kurzynski, M.; Lohmander, L.; Englund, M. (2012)
      Objective: To develop a system for predicting the progression of radiographic knee osteoarthritis (OA) using tibial trabecular bone texture. Methods: We studied 203 knees with (n = 68) or without (n = 135) radiographic ...
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      There is ongoing research directed towards the development of cheap and reliable decision support systems for the detection and prediction of osteoarthritis (OA) in knee joints. Fractal analysis of trabecular bone texture ...
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