<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norbert Hantos</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">George Bebis</style></author><author><style face="normal" font="default" size="100%">Richard Boyle</style></author><author><style face="normal" font="default" size="100%">Bahram Parvin</style></author><author><style face="normal" font="default" size="100%">Darko Koracin</style></author><author><style face="normal" font="default" size="100%">Ronald Chung</style></author><author><style face="normal" font="default" size="100%">Riad Hammound</style></author><author><style face="normal" font="default" size="100%">Muhammad Hussain</style></author><author><style face="normal" font="default" size="100%">Tan Kar-Han</style></author><author><style face="normal" font="default" size="100%">Roger Crawfis</style></author><author><style face="normal" font="default" size="100%">Daniel Thalmann</style></author><author><style face="normal" font="default" size="100%">David Kao</style></author><author><style face="normal" font="default" size="100%">Lisa Avila</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Image enhancement by median filters in algebraic reconstruction methods: an experimental study</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Visual Computing</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><short-title><style face="normal" font="default" size="100%">LNCS</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov-Dec 2010</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">6455</style></number><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Las Vegas, NV, USA</style></pub-location><pages><style face="normal" font="default" size="100%">339 - 348</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-17276-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;abstract-content formatted&quot; itemprop=&quot;description&quot;&gt;&lt;p class=&quot;a-plus-plus&quot;&gt;Algebraic methods for image reconstruction provide good solutions even if only few projections are available. However, they can create noisy images if the number of iterations or the computational time is limited. In this paper, we show how to decrease the effect of noise by using median filters during the iterations. We present an extensive study by applying filters of different sizes and in various times of the reconstruction process. Also, our test images are of different structural complexity. Our study concentrates on the ART and its discrete variant DART reconstruction methods.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000290358400035ScopusID: 78650793785doi: 10.1007/978-3-642-17277-9_35</style></notes></record></records></xml>