A design and implementation of an efficient, parallel watershed algorithm for affinity graphs
Name
757176741-MIT.pdf
Description
Full printable version
Size
3.51 MB
Format
Adobe PDF
Checksum (MD5)
694652b92d869dec5b42e79aeb2890a7
Author(s)
Zlateski, Aleksandar
Advisor(s)
H. Sebastian Seung.
Alternative Title
Efficient watershed algorithm implementation for large affinity graphs
Date Issued
2011
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I designed and implemented an efficient, parallel, generalized watershed algorithm for hierarchical segmentation of affinity graphs. By introducing four variable parameters the algorithm enables us to use previous knowledge about the input graph in order to achieve better results. The algorithm is very suitable for hierarchical segmentintation of large scale 3D images of the brain tissue obtained by electron microscopy making it an essential tool for reconstructing the brain's neural-networks called connectomes. The algorithm was fully implemented in C++ and tested on a currently largest available affinity graph of size 90GB on which no existent watershed implementation could be applied.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 43).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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