Automated Seed Point Selection in Confocal Image Stacks of Neuron Cells

This paper provides a fully automated method of finding high-quality seed points in 3D space from a stack of images of neuron cells. These seed points may then be used as initial starting points for automated local tracing algorithms, removing a time consuming required user interaction in current methodologies. Methods to collapse the search space and provide rudimentary topology estimates are also presented.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2013

Author dc:creator

• Bilodeau, Gregory Peter

Chair dc:contributor.committeechair

• Egyhazy, Csaba J.

Committee members dc:contributor.committeemember

• Kulczycki, Gregory W.
• Chen, Ing-Ray

• Neuron tracing
• DIADEM
• image analysis

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:315

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/23328