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Coronary artery calcification is known to be a strong and independent forecaster of CAD. Hence, coronary computer tomography angiography (CTA) has become a fundamental noninvasive imaging tool to characterize coronary artery plaques. In this article, an automated algorithm is presented to uncover the presence of a calcified plaque, using 2060 CTA images acquired from 60 patients. Higher\u2010order spectra cumulants were extracted from each image, thereby providing 2448 descriptive features per image. The features were then reduced using numerous well\u2010established techniques, and ranked according to <jats:italic>t<\/jats:italic> value. Subsequently, the reduced features were input to several classifiers to achieve the best diagnostic accuracy with a minimum number of features. Optimal results were obtained using the support vector machine with a radial basis function, having 22 features obtained with the multiple factor analysis feature reduction algorithm. The accuracy, positive predictive value, sensitivity, and specificity obtained were 95.83%, 97.05%, 94.54%, and 97.13%, respectively. Based on these results, the technique could be useful to automatically and accurately identify calcified plaque evident in CTA images, and may therefore become an important tool to help reduce procedural costs and patient radiation dose.<\/jats:p>","DOI":"10.1002\/ima.22369","type":"journal-article","created":{"date-parts":[[2019,9,14]],"date-time":"2019-09-14T11:03:35Z","timestamp":1568459015000},"page":"285-297","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated detection of calcified plaque using higher\u2010order spectra cumulant technique in computer tomography angiography images"],"prefix":"10.1002","volume":"30","author":[{"given":"U Rajendra","family":"Acharya","sequence":"first","affiliation":[{"name":"Department of Electronics and Computer Engineering Ngee Ann Polytechnic  Singapore Singapore"},{"name":"Department of Biomedical Engineering School of Science and Technology, Singapore University of Social Sciences  Singapore Singapore"},{"name":"International Research Organization for Advanced Science and Technology (IROAST) Kumamoto University  Kumamoto Japan"}]},{"given":"Kristen M.","family":"Meiburger","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications Politecnico di Torino  Turin Italy"}]},{"given":"Joel E. W.","family":"Koh","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering Ngee Ann Polytechnic  Singapore Singapore"}]},{"given":"Edward J.","family":"Ciaccio","sequence":"additional","affiliation":[{"name":"Department of Medicine Columbia University Medical Center  New York New York"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0091-6049","authenticated-orcid":false,"given":"Jahmunah","family":"Vicnesh","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering Ngee Ann Polytechnic  Singapore Singapore"}]},{"given":"Sock K.","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Biomedical Imaging, Faculty of Medicine University of Malaya  Kuala Lumpur Malaysia"},{"name":"Faculty of Medicine, University of Malaya University of Malaya Research Imaging Centre (UMRIC)  Kuala Lumpur Malaysia"}]},{"given":"Jeannie H. 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