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dc.contributor.authorWoloszynski, Tomasz
dc.contributor.authorPodsiadlo, Pawel
dc.contributor.authorKurzynski, M.
dc.contributor.authorStachowiak, Gwidon
dc.date.accessioned2017-01-30T12:38:17Z
dc.date.available2017-01-30T12:38:17Z
dc.date.created2014-03-09T20:00:41Z
dc.date.issued2010
dc.identifier.citationWoloszynski, 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.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/23628
dc.identifier.doi10.1118/1.3373522
dc.description.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.

dc.publisherAmerican Association of Physicists in Medicine
dc.subjectScale-space
dc.subjectDissimilarity measure
dc.subjectImage classification
dc.subjectRadiographs
dc.subjectKnee osteoarthritis
dc.titleA signature dissimilarity measure for trabecular bone texture in knee radiographs
dc.typeJournal Article
dcterms.source.volume37
dcterms.source.number5
dcterms.source.startPage2030
dcterms.source.endPage2042
dcterms.source.issn00942405
dcterms.source.titleMedical Physics
curtin.department
curtin.accessStatusFulltext not available


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