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

Richard J. Giuly | Zendy; Keunyoung Kim | Zendy; Mark H. Ellisman | Zendy

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

Author(s) -

Richard J. Giuly,

Keunyoung Kim,

Mark H. Ellisman

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt154

Subject(s) - computer science , python (programming language) , segmentation , scalability , source code , image segmentation , process (computing) , workforce , artificial intelligence , computer vision , data mining , database , programming language , economics , economic growth

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.

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