Design and Evaluation of Interactive Proofreading Tools for Connectomics

摘要

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 , a fully-featured single-user desktop application for proofreading, and , a multi-user web-based application for collaborative proofreading. We evaluate the accuracy and speed of , and , 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 , when given the same amount of time. In addition, all participants using reported better usability. We discuss our findings and provide an analysis of requirements for designing visual proofreading software.