Extraction of texture features from x-ray images: case of osteoarthritis detection
Affiliation
University of BedfordshireIssue Date
2018-09-29Subjects
feature extraction
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Third International Congress on Information and Communication TechnologyAbstract
Texture 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.Citation
Akter 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.Publisher
SpringerAdditional Links
https://link.springer.com/chapter/10.1007/978-981-13-1165-9_13Type
Conference papers, meetings and proceedingsLanguage
enISSN
2194-5357EISSN
2194-5365ae974a485f413a2113503eed53cd6c53
10.1007/978-981-13-1165-9_13