DP2: Distributed 3D image segmentation using micro-labor workforce.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 23574738.
- Also identified by DOI 10.1093/bioinformatics/btt154 and PMC identifier 3654713.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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. Python-based code for non-commercial use and test data are available in the source archive at https://sites.google.com/site/imagecrowdseg/. rgiuly@ucsd.edu Supplementary data are available at Bioinformatics online.
Medical subject headings
- Imaging, Three-Dimensional
- Software