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Automatic quantification of cell viability in hippocampal organotypic cultures
Descriptive
TitleInfo
Title
Automatic quantification of cell viability in hippocampal organotypic cultures
Name
(type = personal)
NamePart
(type = family)
Kannan
NamePart
(type = given)
Aparna
NamePart
(type = date)
1992-
DisplayForm
Aparna Kannan
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Shreiber
NamePart
(type = given)
David
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David Shreiber
Affiliation
Advisory Committee
Role
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(authority = RULIB)
chair
Name
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(type = family)
Hacihaliloglu
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(type = given)
Ilker
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Ilker Hacihaliloglu
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Advisory Committee
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(authority = RULIB)
internal member
Name
(type = personal)
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(type = family)
Pierce
NamePart
(type = given)
Mark
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Mark Pierce
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
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NamePart
Rutgers University
Role
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(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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school
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Text
Genre
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theses
OriginInfo
DateCreated
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2014
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2014-10
CopyrightDate
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2014
Place
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(type = code)
xx
Language
LanguageTerm
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(type = code)
eng
Abstract
(type = abstract)
Traumatic Brain Injury (TBI) is a leading cause of disability with many different types of forces. Because the brain is made of up interconnected nerve cells, injury from one area of brain can easily spread throughout the rest of the brain. In order to study this effect in this paper, we use hippocampal organotypic cell cultures. To analyze how secondary and further injury is spread in the brain due to TBI, specific regions of interest are outlined using bright-field microscopy images and analyzed for cell death through fluorescent images. Because of the bias in segmenting these specific regions, and the darkening of bright-field images from necrosis, there is a need for the development of an automatic cell viability analysis method. We first create silhouette masks identifying the area of the hippocampus within the bright-field images. Then, we align these masks of these images between two time points – one before experimentation and another 24 hours after lab experimentation - using Mattes Mutual Information registration to help analyze corresponding regions between time points. We also use relative intensity gradients and contrast enhancement to help isolate the specific regions of interest within the hippocampus, and then aligned the regions of interest between time points using the transformation discovered through the registration process. Finally, we look within these extracted regions for cell viability in fluorescent images taken after experimentation and calculate the ratio between the area of the fluorescent region extracted and the area of the segmented region. Comparing the results from this method with manual segmentation by experienced users, we discover an average of 12% error in segmentation and 2% error in registration. The overall method took an average of 7 minutes per image, which compared to the time it takes complete manually, allows users to conserve time and prevent user-to-user bias in segmentation.
Subject
(authority = RUETD)
Topic
Biomedical Engineering
Subject
(authority = ETD-LCSH)
Topic
Brain--Wounds and injuries
Subject
(authority = ETD-LCSH)
Topic
Hippocampus (Brain)--Physiology
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_5905
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (ix, 42 p. : ill.)
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Aparna Kannan
RelatedItem
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3S75DT8
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
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The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Kannan
GivenName
Aparna
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2014-09-25 10:11:20
AssociatedEntity
Name
Aparna Kannan
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime
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(qualifier = exact);
(point = start)
2014-10-31
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = end)
2015-10-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2015.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
(ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem
(VERSION = 5.1)
windows xp
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