SNEMI3D: 3D Segmentation of neurites in EM images

<p>In this challenge, a full stack of electron microscopy (EM) slices will be used to train <strong>machine-learning algorithms</strong> for the purpose of <strong>automatic</strong> <strong>segmentation of neurites in 3D</strong>. This imaging technique visualizes the resulting volumes in a highly anisotropic way, i.e., the x- and y-directions have a high resolution, whereas the z-direction has a low resolution, primarily dependent on the precision of serial cutting. EM produces the images as a projection of the whole section, so some of the neural membranes that are not orthogonal to a cutting plane can appear very blurred. None of these problems led to major difficulties in the manual labeling of each neurite in the image stack by an expert human neuro-anatomist.</p> <p>In order to gauge the current state-of-the-art in automated neurite segmentation on EM and compare between different methods, we are organizing a 3D Segmentation of neurites in EM images (SNEMI3D) challenge in conjunction with the<a href="http://www.biomedicalimaging.org/2013/program/isbi-challenges/"> ISBI 2013 conference</a>. For this purpose, we are making available a large training dataset of mouse cortex in which the neurites have been manually delineated. In addition, we also provide a test dataset where the 3D labels are not available. The aim of the challenge is to compare and rank the different competing methods based on their<strong> object classification accuracy</strong> in three dimensions.</p> <p>The <strong>image&nbsp;data</strong> used in the challenge was produced by <a href="http://lichtmanlab.fas.harvard.edu/">Lichtman Lab at Harvard University</a> (Daniel R. Berger,&nbsp;Richard Schalek,&nbsp;Narayanan &quot;Bobby&quot; Kasthuri,&nbsp;Juan-Carlos Tapia,&nbsp;Kenneth Hayworth, Jeff W. Lichtman) and manually annotated by&nbsp;<a href="http://lichtmanlab.fas.harvard.edu/people/daniel-berger">Daniel R. Berger</a>. Their corresponding biological findings were published in <a href="http://www.ncbi.nlm.nih.gov/pubmed/26232230">Cell (2015)</a>.</p>