{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T13:40:45Z","timestamp":1740058845957,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>Lung disease is a growing disease and hence needs lot of attention. It is difficult to delineate the boundary of the lung when it is imaged through X-ray due to poor resolution. Hence, computer aided diagnosis (CAD) is preferred as it assists the radiologists in efficient diagnosis. In this work, a novel supervised classification technique is proposed using histogram of oriented gradient (HOG) and neighborhood preserving embedding (NPE). Our method is evaluated using 2000 chest X-ray images and can efficiently classify normal and abnormal classes with a promising performance of 97.95% accuracy, using support vector machine (SVM) classifier.<\/jats:p>","DOI":"10.3233\/978-1-61499-900-3-1018","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":0,"title":["Automated Detection of Lung Nodules Using HOG Technique with Chest X-Ray Images"],"prefix":"10.3233","author":[{"family":"Raghavendra U.","sequence":"additional","affiliation":[]},{"family":"Gudigar Anjan","sequence":"additional","affiliation":[]},{"family":"Rao Tejaswi N.","sequence":"additional","affiliation":[]},{"family":"Fujita Hamido","sequence":"additional","affiliation":[]},{"family":"Acharya U. Rajendra","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T13:01:07Z","timestamp":1740056467000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-899-0&spage=1018&doi=10.3233\/978-1-61499-900-3-1018"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-900-3-1018","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2018]]}}}