1.0Centre for Computational Personalized Medicinehttps://sano.sciencesano.sciencehttps://sano.science/author/sano-science/rich600338<blockquote class="wp-embedded-content" data-secret="zGT5QmDJal"><a href="https://sano.science/research/brain-tumor-classification-and-image-translation/">Brain tumor classification and image​ translation</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://sano.science/research/brain-tumor-classification-and-image-translation/embed/#?secret=zGT5QmDJal" width="600" height="338" title="“Brain tumor classification and image​ translation” — Centre for Computational Personalized Medicine" data-secret="zGT5QmDJal" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript"> /* <![CDATA[ */ /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); //# sourceURL=https://sano.science/wp-includes/js/wp-embed.min.js /* ]]> */ </script> Gliomas, aggressive, highly heterogeneous brain tumors, require precise grading for effective treatment. The role of myeloid cells in the tumor microenvironment (TME) is crucial for glioma progression and patient prognosis, emphasizing the need for advanced diagnostic tools. We propose automatic multiclass histology classification with quantification and learning of TME features.