http://www.nitrc.org/forum/forum.php?forum_id=2951 <p class="abstract"><div class="Abstract" lang="en"><a name="Abs1"></a><span class="AbstractHeading">Abstract&nbsp;&nbsp;</span><div class="normal">Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets. </div> </div></p><ul> <li><span class="labelName">Content Type </span><span class="labelValue">Journal Article</span></li><li>Category Original Article</li><li>Pages 247-261</li><li>DOI 10.1007/s12021-011-9120-3</li><li><span class="labelName">Authors</span><ul> <li>Ting Zhao, Qiushi Academy for Advanced Studies, Zhejiang University, 38 ZheDa Road, Hangzhou, 310027 China</li><li>Jun Xie, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Fernando Amat, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Nathan Clack, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Parvez Ahammad, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Hanchuan Peng, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Fuhui Long, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li><li>Eugene Myers, HHMI Janelia Farm Research Campus, 19700 Helix Dr., Ashburn, VA 20147, USA</li> </ul></li> </ul><ul class="parents"> <ul class="details"> <li><span class="header labelName">Journal </span><span class="labelValue"><a href="http://www.springerlink.com/content/120559/">Neuroinformatics</a></span></li><li><span class="labelName">Online ISSN </span><span class="labelValue">1559-0089</span></li><li><span class="labelName">Print ISSN </span><span class="labelValue">1539-2791</span></li> </ul><ul class="details"> <li><span class="header labelName">Journal Volume </span><span class="labelValue">Volume 9</span></li> </ul><ul class="details"> <li><span class="header labelName">Journal Issue </span><span class="labelValue"><a href="http://www.springerlink.com/content/q1w234205257/">Volume 9, Numbers 2-3</a></span></li> </ul> </ul> en-us Copyright 2000-2026 NITRC OSI Sun, 19 Apr 2026 20:46:52 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator