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ABSTRACT: Summary
This application note describes a new scalable semi-automatic approach, the Dual Point Decision Process, for segmentation of 3D structures contained in 3D microscopy. The segmentation problem is distributed to many individual workers such that each receives only simple questions regarding whether two points in an image are placed on the same object. A large pool of micro-labor workers available through Amazon's Mechanical Turk system provides the labor in a scalable manner.Availability and implementation
Python-based code for non-commercial use and test data are available in the source archive at https://sites.google.com/site/imagecrowdseg/.Contact
rgiuly@ucsd.eduSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Giuly RJ
PROVIDER: S-EPMC3654713 | biostudies-literature | 2013 May
REPOSITORIES: biostudies-literature
Giuly Richard J RJ Kim Keun-Young KY Ellisman Mark H MH
Bioinformatics (Oxford, England) 20130410 10
<h4>Summary</h4>This application note describes a new scalable semi-automatic approach, the Dual Point Decision Process, for segmentation of 3D structures contained in 3D microscopy. The segmentation problem is distributed to many individual workers such that each receives only simple questions regarding whether two points in an image are placed on the same object. A large pool of micro-labor workers available through Amazon's Mechanical Turk system provides the labor in a scalable manner.<h4>Av ...[more]