1.0German Conference on Medical Image Computinghttps://www.bvm-conf.org/de/rich600338<blockquote class="wp-embedded-content" data-secret="MCXYvO259T"><a href="https://www.bvm-conf.org/de/bvm2021/postersession/poster51/">Poster 51</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.bvm-conf.org/de/bvm2021/postersession/poster51/embed/#?secret=MCXYvO259T" width="600" height="338" title="„Poster 51“ – German Conference on Medical Image Computing" data-secret="MCXYvO259T" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! 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://www.bvm-conf.org/wp-includes/js/wp-embed.min.js </script> Abstract: JBFnet: Low Dose CT-denoising by Trainable Joint Bilateral Filtering Mayank Patwari, Ralf Gutjahr, Rainer Raupach, Andreas Maier Friedrich-Alexander Universität Erlangen-Nürnberg, Lehrstuhl für Mustererkennung Abstract Deep neural networks have shown great success in low dose CT denoising. However, most of these deep neural networks have several hundred thousand trainable parameters. This, combined with the inherent…https://www.bvm-conf.org/wp-content/uploads/2020/09/cropped-BVM-Logo.png964964