1.0BIG-S2/bigs2Tengfei Li/bigs2/author/tengfei/Tissue Microarray - BIG-S2rich600338<blockquote class="wp-embedded-content" data-secret="PqMzTPK82e"><a href="/bigs2/projects/tissue-microarray/">Tissue Microarray</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="/bigs2/projects/tissue-microarray/embed/#?secret=PqMzTPK82e" width="600" height="338" title="“Tissue Microarray” — BIG-S2" data-secret="PqMzTPK82e" 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); /* ]]> */ </script> TMA-DDLM: Tissue Microarray Analysis via A Deep Dictionary Learning Method   Introduction TMA-DDLM is a algorithm used to extract morphological features from Tissue Microarray images and make predictions for the important clinical parameters. Specifically, image features are extracted by deep dictionary learning method, which will be combined with the demographic covariates and make the final … Read more/bigs2/wp-content/uploads/sites/822/2018/09/project_TMA_pipeline-300x138.png