{"id":1201,"date":"2026-01-25T19:30:28","date_gmt":"2026-01-25T19:30:28","guid":{"rendered":"https:\/\/www.cs.ubbcluj.ro\/~meco\/linear-discriminant-analysis-tumour-classification-for-unsupervised-segmented-mammographies-2023\/"},"modified":"2026-02-01T12:08:10","modified_gmt":"2026-02-01T12:08:10","slug":"linear-discriminant-analysis-tumour-classification-for-unsupervised-segmented-mammographies-2023","status":"publish","type":"post","link":"https:\/\/www.cs.ubbcluj.ro\/~meco\/linear-discriminant-analysis-tumour-classification-for-unsupervised-segmented-mammographies-2023\/","title":{"rendered":"Linear Discriminant Analysis Tumour Classification for Unsupervised Segmented Mammographies (2023)"},"content":{"rendered":"<div class=\"entry-content\">\n<p>International Conference on Knowledge-Based Intelligent Information &amp; Engineering Systems<\/p>\n<h2>Authors<\/h2>\n<p>Cristiana Moroz-Dubenco, A. Andreica<\/p>\n<h2>Abstract<\/h2>\n<p>Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing the mammography, the region of interest is identified using an unsupervised manner. Textural features are extracted from the Gray-Level Co-occurrence Matrix and used with the Linear Discriminant Analysis classifier, obtaining a diagnosis: benign or malignant. The proposed system is tested on the Mini-MIAS dataset, reaching an accuracy score of 95% and a precision and specificity of 100%.<\/p>\n<h2>Citation<\/h2>\n<pre class=\"wp-block-preformatted\">@Inproceedings{Moroz-Dubenco2023LinearDA,\n author = {Cristiana Moroz-Dubenco and A. Andreica},\n booktitle = {International Conference on Knowledge-Based Intelligent Information &amp; Engineering Systems},\n title = {Linear Discriminant Analysis Tumour Classification for Unsupervised Segmented Mammographies},\n year = {2023}\n}<\/pre>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Between 2015 and 2020, 7.8 million women were diagnosed with breast cancer. If the cancer is discovered early, it can be completely cured. Computer-aided detection and diagnosis systems are a helpful tool. We propose such a system: after pre-processing the mammography, the region of interest is identified using an unsupervised manner. Textural features are extracted from the Gray-Level Co-occurrence Matrix and used with the Linear Discriminant Analysis classifier, obtaining a diagnosis: benign or malignant. The proposed system is tested on the Mini-MIAS dataset, reaching an accuracy score of 95% and a precision and specificity of 100%.<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[45,40,9,30,46],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1201"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/comments?post=1201"}],"version-history":[{"count":1,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1201\/revisions"}],"predecessor-version":[{"id":1477,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1201\/revisions\/1477"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media?parent=1201"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/categories?post=1201"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/tags?post=1201"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}