Design and Evaluation of Interactive Proofreading Tools for Connectomics
IEEE SciVis 2014
Daniel Haehn Seymour Knowles-Barley Mike Roberts Johanna
Beyer
Narayanan Kasthuri Jeff W. Lichtman Hanspeter Pfister
Harvard University Harvard University Stanford University Harvard University Harvard University Harvard University Harvard University
teaser
Proofreading refers to the manual correction of automatic segmentations of image data. In connectomics, electron microscopy data is acquired at nanometer-scale resolution and results in very large image volumes of brain tissue that require fully automatic segmentation algorithms to identify cell boundaries. However, these algorithms require hundreds of corrections per cubic micron of tissue. Even though this task is time consuming, it is fairly easy for humans to perform corrections through splitting, merging, and adjusting segments during proofreading. In this paper we present the design and implementation of Mojo, a fully-featured single-user desktop application for proofreading, and Dojo, a multi-user web-based application for collaborative proofreading. We evaluate the accuracy and speed of Mojo, Dojo, and Raveler, a proofreading tool from Janelia Farm, through a quantitative user study. We designed a between-subjects experiment and asked non-experts to proofread neurons in a publicly available connectomics dataset. Our results show a significant improvement of corrections using web-based Dojo even in comparison to fully manual expert segmentation, when given the same amount of time. In addition, all participants using Dojo reported better usability. We discuss our findings and provide an analysis of requirements for designing visual proofreading software.

bibtex

@ARTICLE{haehn_dojo_2014,
author = {D. Haehn and S. Knowles-Barley and M. Roberts and
J. Beyer and N. Kasthuri and J.W. Lichtman and H. Pfister},
title = {Design and Evaluation of Interactive
Proofreading Tools for Connectomics},
journal = {IEEE Transactions on Visualization and
Computer Graphics (Proceedings IEEE SciVis 2014)},
year = {2014},
volume = {20},
number = {12},
pages = {2466--2475},
}

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