Dataset Information

DP2: Distributed 3D image segmentation using micro-labor workforce.

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.edu

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Giuly RJ

PROVIDER: S-EPMC3654713 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

DP2: Distributed 3D image segmentation using micro-labor workforce.

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]

PMID: 23574738

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Dataset Information

DP2: Distributed 3D image segmentation using micro-labor workforce.

Summary

Availability and implementation

Contact

Supplementary information

Publications

DP2: Distributed 3D image segmentation using micro-labor workforce.

Similar Datasets

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