Extraction of texture features from x-ray images: case of osteoarthritis detection
AffiliationUniversity of Bedfordshire
MetadataShow full item record
Other TitlesThird International Congress on Information and Communication Technology
AbstractTexture features quantitatively represent patterns of interest in image analysis and interpretation. Texture features can vary so largely that the analysis leads to interpretation errors and undesirable consequences. In such cases, finding of informative features becomes problematic. In medical imaging, the texture features were found useful for representing variations in patterns of pixel intensity, which were correlated with pathological changes. In this paper, we describe a new approach to extracting the texture features which are represented on the basis of Zernike orthogonal polynomials. We report the preliminary results which were obtained for a case of osteoarthritis detection in X-ray images using a deep learning paradigm known as group method of data handling.
CitationAkter M, Jakaite L (2019) 'Extraction of texture features from x-ray images: case of osteoarthritis detection', Third International Congress on Information and Communication Technology ICICT 2018 - London, Springer.
TypeConference papers, meetings and proceedings