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Massachusetts Institute of Technology

Omni : visualizing and editing large-scale volume segmentations of neuronal tissue

Abstract

dc:description.abstract

Connectomics researchers examine images of the brain in order to determine the structure of neuronal networks. As imaging techniques improve, images are growing in size and resolution - but they are also outgrowing the capacity of existing software to view these images. In response to this problem, this thesis presents OMNI: an application for viewing and editing large connectomic image volumes. OMNI employs pre-processing and caching techniques to allow researchers to examine large image volumes at multiple viewpoints and resolutions. But OMNI is also a full-fledged navigation and editing environment, incorporating the suggestions of connectomics researchers into a simple and flexible user interface design. The OMNI user interface features multiple synchronized display windows and a novel project inspector widget that facilitates project interaction. The 2D navigation and editing modules use OpenGL textures to display image slices from large image volumes and feature a texture management system that includes a threaded texture cache. Editing is performed by painting voxels in a viewing window and allows the user to edit existing neuron tracings or create new ones. The development of OMNI gives connectomics researchers a way to view detailed images of the nervous system and enables them to trace neural pathways through these large images. By studying the structure of individual neurons and groups of neurons, researchers can approach a better understanding of neuron function and the development of the brain.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Shearer, Rachel Welles
Advisor dc:contributor.advisor
  • Sebastian Seung.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/53139
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/53139

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Shearer, Rachel Welles. Omni : visualizing and editing large-scale volume segmentations of neuronal tissue. Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53139