{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T01:27:38Z","timestamp":1751765258813,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>Liver cirrhosis is a commonly chronic disease that often requires checking liver pathological microscopic images. To reduce the intensity of the work of doctors, pre-classification work needs to be issued and in this paper, related liver microscopic image classification analysis was proposed. Firstly, the extraction methods of mice liver images were taken using different features for different image features, and secondly, image features were obtained to form the original data-set; finally, the image classification experiments were conducted using gray level co-occurrence matrix (GLCM) and a developed support vector machine (SVM). The best classification model derived from the established characteristics is that GLCM performed the highest accuracy of classification; the training model using 11 features was accurately that only trained by 8 GLCMs. The experimental results preliminarily verified the feasibility of the method used in the experiment of classifying liver microscopic images of mice, and laid the foundation for further construction of computer aided diagnosis system.<\/jats:p>","DOI":"10.3233\/978-1-61499-785-6-509","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:24Z","timestamp":1740133644000},"source":"Crossref","is-referenced-by-count":1,"title":["Mice Liver Cirrhosis Microscopic Image Analysis Using Gray Level Co-Occurrence Matrix and Support Vector Machines"],"prefix":"10.3233","author":[{"family":"Wang Yu","sequence":"additional","affiliation":[]},{"family":"Cao Luying","sequence":"additional","affiliation":[]},{"family":"Dey Nilanjan","sequence":"additional","affiliation":[]},{"family":"Ashour Amira S.","sequence":"additional","affiliation":[]},{"family":"Shi Fuqian","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Technology and Intelligent Transportation Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:07:33Z","timestamp":1740136053000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-784-9&spage=509&doi=10.3233\/978-1-61499-785-6-509"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-785-6-509","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}