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<oembed><version>1.0</version><provider_name>German Conference on Medical Image Computing</provider_name><provider_url>https://www.bvm-conf.org/de/</provider_url><title>Poster 20 &#x2014; German Conference on Medical Image Computing</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="EoX3yvGhNc"&gt;&lt;a href="https://www.bvm-conf.org/de/bvm2021/postersession/poster20/"&gt;Poster 20&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.bvm-conf.org/de/bvm2021/postersession/poster20/embed/#?secret=EoX3yvGhNc" width="600" height="338" title="&#x201E;Poster 20&#x201C; &#x2013; German Conference on Medical Image Computing" data-secret="EoX3yvGhNc" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Combining Reconstruction and Edge Detection in Computed Tomography J&#xFC;rgen Frikel, Simon G&#xF6;ppel, Markus Haltmeier Ostbayerische Technische Hochschule Regensburg Abstract We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backprojection algorithm. In our second method we employ l1-regularization&hellip;</description><thumbnail_url>https://www.bvm-conf.org/wp-content/uploads/2020/09/cropped-BVM-Logo.png</thumbnail_url><thumbnail_width>964</thumbnail_width><thumbnail_height>964</thumbnail_height></oembed>
