{"id":71580,"date":"2024-11-26T11:45:09","date_gmt":"2024-11-26T09:45:09","guid":{"rendered":"https:\/\/www.iemn.fr\/?p=71580"},"modified":"2024-11-26T11:46:41","modified_gmt":"2024-11-26T09:46:41","slug":"these-bilel-guetarn","status":"publish","type":"post","link":"https:\/\/www.iemn.fr\/en\/a-la-une\/these-bilel-guetarn.html","title":{"rendered":"Thesis by Bilel GUETARNI: \"Machine learning based classification for identifying lymphoma cancer cells in histopathologic images\" on 2\/12 10.00 a.m."},"content":{"rendered":"<div id='layer_slider_1'  class='avia-layerslider main_color avia-shadow  avia-builder-el-0  el_before_av_heading  avia-builder-el-first  container_wrap sidebar_right'  style='height: 261px;'  ><div id=\"layerslider_58_qmnj22w6239p\" data-ls-slug=\"homepageslider\" class=\"ls-wp-container fitvidsignore ls-selectable\" style=\"width:1140px;height:260px;margin:0 auto;margin-bottom: 0px;\"><div class=\"ls-slide\" data-ls=\"duration:6000;transition2d:5;\"><img loading=\"lazy\" decoding=\"async\" width=\"2600\" height=\"270\" src=\"https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1.jpg\" class=\"ls-bg\" alt=\"\" srcset=\"https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1.jpg 2600w, https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1-300x31.jpg 300w, https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1-768x80.jpg 768w, https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1-1030x107.jpg 1030w, https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1-1500x156.jpg 1500w, https:\/\/www.iemn.fr\/wp-content\/uploads\/2019\/01\/sliders_news1-705x73.jpg 705w\" sizes=\"auto, (max-width: 2600px) 100vw, 2600px\" \/><ls-layer style=\"font-size:14px;text-align:left;font-style:normal;text-decoration:none;text-transform:none;font-weight:700;letter-spacing:0px;border-style:solid;border-color:#000;background-position:0% 0%;background-repeat:no-repeat;width:180px;height:30px;left:0px;top:231px;line-height:32px;color:#ffffff;border-radius:6px 6px 6px 6px;padding-left:50px;background-color:rgba(0, 0, 0, 0.57);\" class=\"ls-l ls-ib-icon ls-text-layer\" data-ls=\"minfontsize:0;minmobilefontsize:0;\"><i class=\"fa fa-quote-right\" style=\"color:#ffffff;margin-right:0.8em;font-size:1em;transform:translateY( -0.125em );\"><\/i>ACTUALITES<\/ls-layer><\/div><\/div><\/div><div id='after_layer_slider_1'  class='main_color av_default_container_wrap container_wrap sidebar_right'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-71580'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-k5dohoxw-ac2e9c4dcd1ea3892a581d5dfb9e4a24\">\n#top .av-special-heading.av-k5dohoxw-ac2e9c4dcd1ea3892a581d5dfb9e4a24{\nmargin:0 0 10px 0;\npadding-bottom:4px;\n}\nbody .av-special-heading.av-k5dohoxw-ac2e9c4dcd1ea3892a581d5dfb9e4a24 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-k5dohoxw-ac2e9c4dcd1ea3892a581d5dfb9e4a24 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-k5dohoxw-ac2e9c4dcd1ea3892a581d5dfb9e4a24 av-special-heading-h4  avia-builder-el-1  el_after_av_layerslider  el_before_av_hr  avia-builder-el-first  av-linked-heading'><h4 class='av-special-heading-tag'  itemprop=\"headline\"  >Thesis by Bilel GUETARNI: \"Machine learning based classification for identifying lymphoma cancer cells in histopathologic images\" 2\/12 10.00 am<\/h4><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-18u73nj-dad6a947580930e400fc42ba200e80f1\">\n#top .hr.av-18u73nj-dad6a947580930e400fc42ba200e80f1{\nmargin-top:5px;\nmargin-bottom:5px;\n}\n.hr.av-18u73nj-dad6a947580930e400fc42ba200e80f1 .hr-inner{\nwidth:100%;\n}\n<\/style>\n<div  class='hr av-18u73nj-dad6a947580930e400fc42ba200e80f1 hr-custom  avia-builder-el-2  el_after_av_heading  el_before_av_textblock  hr-left hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<section  class='av_textblock_section av-jriy64i8-fd5f2e9d63bf552d6910d12f255eb26e'   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" >\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-13ewzjw-68e036126b913e5028f77311dc66b825\">\n.av_font_icon.av-13ewzjw-68e036126b913e5028f77311dc66b825{\ncolor:#bfbfbf;\nborder-color:#bfbfbf;\n}\n.av_font_icon.av-13ewzjw-68e036126b913e5028f77311dc66b825 .av-icon-char{\nfont-size:60px;\nline-height:60px;\n}\n<\/style>\n<span  class='av_font_icon av-13ewzjw-68e036126b913e5028f77311dc66b825 avia_animate_when_visible av-icon-style- avia-icon-pos-left avia-icon-animate'><span class='av-icon-char' aria-hidden='true' data-av_icon='\ue8c9' data-av_iconfont='entypo-fontello' ><\/span><\/span>\n<p><strong>Thesis Bilel GUETARNI<br \/>\n<\/strong><\/p>\n<p>Defence: 2 December 10:00<strong><br \/>\n<\/strong>IEMN Amphitheatre<\/p>\n<\/div><\/section>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-jtefqx33-6db969b2e204313ebd62331ed4fc69ec\">\n#top .av_textblock_section.av-jtefqx33-6db969b2e204313ebd62331ed4fc69ec .avia_textblock{\nfont-size:15px;\n}\n<\/style>\n<section  class='av_textblock_section av-jtefqx33-6db969b2e204313ebd62331ed4fc69ec'   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><div  class='hr av-kjh3zw-4dff888f744b728a1aca9b3a0971493a hr-default  avia-builder-el-6  avia-builder-el-no-sibling'><span class='hr-inner'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<h5><strong><span style=\"color: #800000;\">Jury<\/span><\/strong><i><\/i><\/h5>\n<table>\n<tbody>\n<tr>\n<td>Dominique COLLARD<\/td>\n<td><\/td>\n<td>Research Director<\/td>\n<td><\/td>\n<td>Universit\u00e9 de Lille<\/td>\n<td><\/td>\n<td>Directeur de th\u00e8se<\/td>\n<\/tr>\n<tr>\n<td>Rachid JENNANE<\/td>\n<td><\/td>\n<td>University Professor<\/td>\n<td><\/td>\n<td>University of Orl\u00e9ans<\/td>\n<td><\/td>\n<td>Rapporteur<\/td>\n<\/tr>\n<tr>\n<td>Nicolas LOM\u00e9NIE<\/td>\n<td><\/td>\n<td>University Professor<\/td>\n<td><\/td>\n<td>Universit\u00e9 Paris Cit\u00e9<\/td>\n<td><\/td>\n<td>Rapporteur<\/td>\n<\/tr>\n<tr>\n<td>Elsa ANGELINI<\/td>\n<td><\/td>\n<td>Professor<\/td>\n<td><\/td>\n<td>T\u00e9l\u00e9com Paris<\/td>\n<td><\/td>\n<td>Examinateur<\/td>\n<\/tr>\n<tr>\n<td>Windal FERYAL<\/td>\n<td><\/td>\n<td>Lecturer and researcher<\/td>\n<td><\/td>\n<td>JUNIA ISEN<\/td>\n<td><\/td>\n<td>Examinateur<\/td>\n<\/tr>\n<tr>\n<td>Halim BENHABILES<\/td>\n<td><\/td>\n<td>Master assistant<\/td>\n<td><\/td>\n<td>IMT Nord Europe, Ecole Mines-T\u00e9l\u00e9com<\/td>\n<td><\/td>\n<td>Examinateur<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h5><strong><span style=\"color: #800000;\">\u00a0<\/span><\/strong><\/h5>\n<h5>Summary:<\/h5>\n<p>Cancer is one of the leading causes of death worldwide, with almost 10 million deaths in 2022, including 1.5 million in Europe. Non-Hodgkin's lymphomas (NHL) are cancers of the immune system and are responsible for more than 250,000 deaths in 2022. In France, the incidence of NHL rose by 21% between 1998 and 2017, and projections predict a significant increase in cases and deaths between now and 2045. Diffuse large B-cell lymphoma (DLBCL) is the most common type of NHL, with two molecular subtypes identified using gene expression profiling techniques: ABC and GCB, the former of which is characterised by a lower survival rate and the need for specific treatment. Several methods exist for determining the LDGC-B subtype, including RT-MLPA (molecular technique), immunohistochemistry and examination of haematoxylin-eosin-stained tissue. However, these methods have limitations in terms of cost, time and accuracy. In this thesis, we propose to investigate the potential of machine learning and deep learning-based methods to improve the diagnosis of LDGC-B patients, both in terms of molecular subtyping and in predicting response to treatment. Using the acquisition of high-resolution histopathological images, we propose two methodologies leading to models capable of predicting a patient's molecular subtype and response to treatment on the basis of these images. The experimental results of this work have shown the potential contribution that these methods can make to the diagnosis of LDGC-B, but also their ability to be generalised to other types of cancer and prediction tasks.<\/p>\n<p align=\"justify\"><strong>Abstract:<\/strong><\/p>\n<p>Cancer is one of the leading causes of death worldwide, with almost 10 million deaths in 2022, including 1.5 million in Europe. Non-Hodgkin's lymphomas (NHL) are cancers of the immune system, and are responsible for more than 250,000 deaths in 2022. In France, the incidence of NHL rose by 21% between 1998 and 2017, and projections predict a significant increase in cases and deaths by 2045. Diffuse large B-cell lymphoma (DLBCL) is the most common type of NHL, with two molecular subtypes identified using gene expression profiling techniques: ABC and GCB, the former of which is characterized by a lower survival rate and the need for specific treatments. Several methods exist to determine the DLBCL subtype, including RT-MLPA (molecular technique), immunohistochemistry and examination of hematoxylin-eosin-stained tissue. Nevertheless, these methods have limitations in terms of cost, time and accuracy. In this thesis, we propose to investigate the potential of machine learning and deep learning-based methods to improve the diagnosis of patients with DLBCL, both in terms of molecular subtyping but also for the prediction of treatment response. Thanks to the acquisition of high-resolution histopathological images, we propose two methodologies leading to models capable of predicting a patient's molecular subtype and treatment response from these images. The experimental results of these works have demonstrated the potential contribution of these methods to the diagnosis of DLBCL, but also their ability to be generalized to other types of cancer and predictive tasks.<\/p>\n<\/div><\/section>","protected":false},"excerpt":{"rendered":"","protected":false},"author":20,"featured_media":71447,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,8,319,65,87,84],"tags":[],"class_list":["post-71580","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-a-la-une","category-actualites","category-actualites2022","category-agenda","category-agenda-en","category-agenda-en-en"],"_links":{"self":[{"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/posts\/71580","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/comments?post=71580"}],"version-history":[{"count":0,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/posts\/71580\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/media\/71447"}],"wp:attachment":[{"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/media?parent=71580"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/categories?post=71580"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iemn.fr\/en\/wp-json\/wp\/v2\/tags?post=71580"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}