{"id":1532,"date":"2022-12-20T13:19:50","date_gmt":"2022-12-20T13:19:50","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1532"},"modified":"2022-12-20T13:21:56","modified_gmt":"2022-12-20T13:21:56","slug":"vol20-no2-art7","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art7\/","title":{"rendered":"Machine Learning Based Sampling of X-Ray Images for a Computer-Aided Detection of Tuberculosis"},"content":{"rendered":"<p>Fernando Ferreira <a href=\"https:\/\/orcid.org\/0000-0003-3455-2316\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Philipp Gaspar <a href=\"https:\/\/orcid.org\/0000-0002-9232-1332\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Rodrigo Torres <a href=\"https:\/\/orcid.org\/0000-0002-1073-0280\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Carlos Eduardo Covas <a href=\"https:\/\/orcid.org\/0000-0003-3158-8495\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Lukas M\u00fcller de Oliveira <a href=\"https:\/\/orcid.org\/0000-0001-7685-502X\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Micael Ver\u00edssimo de Ara\u00fajo <a href=\"https:\/\/orcid.org\/0000-0001-8060-2228\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Jos\u00e9 Manoel de Seixas <a href=\"https:\/\/orcid.org\/0000-0001-5148-7363\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Mayara Bastos <a href=\"https:\/\/orcid.org\/0000-0002-1470-0353\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>&#038; Anete Trajman <a href=\"https:\/\/orcid.org\/0000-0002-4000-4984\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> Computer-Aided Detection software relies on annotated data set of X-rays to be developed. The annotation task is time-consuming and requires extensive know-how. This work presents a sampling method to select the most relevant images, which will be annotated for the development of a tuberculosis (TB) screening platform based on machine learning algorithms. The sampling task optimizes the annotation process by reducing the number of images to be analyzed without compromising the diversity and the significance power of the images in the dataset. We developed an algorithm to select images in a dataset to be annotated, based on similarity and dissimilarity measurements of images. Public TB image dataset was utilized to conduct this research. The experiment consisted of a deep learning feature engineering step, followed by topological analysis based on Self-Organizing Map and K-Means. The effectiveness of the process is evaluated at each of its stages: Classification, clustering and the final sampling algorithm which is based on similarity and dissimilarity features.<\/p>\n<p><strong>Keywords:<\/strong> Deep Learning, CNN, SOM, Clustering, CAD.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol20-no2-art7\">10.21528\/lnlm-vol20-no2-art7<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2022\/12\/vol20-no2-art7.pdf\">vol20-no2-art7.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2022\/12\/vol20-no2-art7.bib\">vol20-no2-art7.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Fernando Ferreira , Philipp Gaspar , Rodrigo Torres , Carlos Eduardo Covas , Lukas M\u00fcller de Oliveira , Micael Ver\u00edssimo de Ara\u00fajo , Jos\u00e9 Manoel de Seixas , Mayara Bastos &#038; Anete Trajman Abstract: Computer-Aided Detection software relies on annotated <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art7\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1512,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1532","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Machine Learning Based Sampling of X-Ray Images for a Computer-Aided Detection of Tuberculosis - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art7\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning Based Sampling of X-Ray Images for a Computer-Aided Detection of Tuberculosis - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Fernando Ferreira , Philipp Gaspar , Rodrigo Torres , Carlos Eduardo Covas , Lukas M\u00fcller de Oliveira , Micael Ver\u00edssimo de Ara\u00fajo , Jos\u00e9 Manoel de Seixas , Mayara Bastos &#038; 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