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A modular microscopic smartphone attachment for imaging and quantification of multiple fluorescent microparticles
Descriptive
TitleInfo
Title
A modular microscopic smartphone attachment for imaging and quantification of multiple fluorescent microparticles
Name
(type = personal)
NamePart
(type = family)
Sami
NamePart
(type = given)
Muhammad Ahsan
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Muhammad Ahsan Sami
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author
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Hassan
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Umer
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Umer Hassan
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Advisory Committee
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chair
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Rutgers University
Role
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degree grantor
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School of Graduate Studies
Role
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school
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Text
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theses
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2021
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2021-05
Language
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English
Abstract
(type = abstract)
Portable smartphone-based fluorescent microscopes are becoming popular because of their
capability to carry out some of the major functionalities offered by regular benchtop microscopes
at a fraction of the cost. However, these smartphone-based microscopes still have a lot of
limitations, such as being limited to only one fluorophore, unavailability of multiple
magnifications to name a few. To overcome these challenges, we present the design of a modular
smartphone-based microscopic attachment. Its modular design allows the user to easily swap
between different sets of filters and lenses, thereby providing the choice between multiple
fluorophores and magnification levels. Furthermore, our proposed attachment can image
specimens on glass slides, cover slips, and microfluidic devices. A 1951 USAF resolution test
target was used to quantify the maximum resolution of the microscope which was found to be 3.9
μm.
The performance of the designed smartphone-based fluorescent microscope was then compared
with regular benchtop microscope by counting fluorescent microparticles imaged. We found the
performance of our design to be satisfactory with an R2 value of 0.99. Additionally, to automate
the quantification of fluorescent microparticles, we developed and trained multiple artificial neural
networks (ANNs) using various training algorithms, and evaluated their performances compared
to the control (ImageJ) and found an R2 value of 0.99. We also performed ANOVA and Tukey’s
post-hoc analysis and found a p-value=0.97 indicating no significant difference.
As a potential application of the designed smartphone-based microscope, we also developed a
PDMS based microfluidic chip to capture and quantify leukocytes from human blood. Anti-human
CD45 antibodies were functionalized inside the capture chamber of the microfluidic chip. These
antibodies captured cells of interest based on antigen antibody interaction. These captured cells
were then made to fluoresce by using a green nuclear stain and the microfluidic chip was imaged
under the smartphone based fluorescent microscope.
capability to carry out some of the major functionalities offered by regular benchtop microscopes
at a fraction of the cost. However, these smartphone-based microscopes still have a lot of
limitations, such as being limited to only one fluorophore, unavailability of multiple
magnifications to name a few. To overcome these challenges, we present the design of a modular
smartphone-based microscopic attachment. Its modular design allows the user to easily swap
between different sets of filters and lenses, thereby providing the choice between multiple
fluorophores and magnification levels. Furthermore, our proposed attachment can image
specimens on glass slides, cover slips, and microfluidic devices. A 1951 USAF resolution test
target was used to quantify the maximum resolution of the microscope which was found to be 3.9
μm.
The performance of the designed smartphone-based fluorescent microscope was then compared
with regular benchtop microscope by counting fluorescent microparticles imaged. We found the
performance of our design to be satisfactory with an R2 value of 0.99. Additionally, to automate
the quantification of fluorescent microparticles, we developed and trained multiple artificial neural
networks (ANNs) using various training algorithms, and evaluated their performances compared
to the control (ImageJ) and found an R2 value of 0.99. We also performed ANOVA and Tukey’s
post-hoc analysis and found a p-value=0.97 indicating no significant difference.
As a potential application of the designed smartphone-based microscope, we also developed a
PDMS based microfluidic chip to capture and quantify leukocytes from human blood. Anti-human
CD45 antibodies were functionalized inside the capture chamber of the microfluidic chip. These
antibodies captured cells of interest based on antigen antibody interaction. These captured cells
were then made to fluoresce by using a green nuclear stain and the microfluidic chip was imaged
under the smartphone based fluorescent microscope.
Subject
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Topic
Electrical and Computer Engineering
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Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_11619
PhysicalDescription
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application/pdf
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text/xml
Extent
1 online resource (xi, 41 pages)
Note
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M.S.
Note
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Includes bibliographical references
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ETD graduate
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
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doi:10.7282/t3-eapz-ac22
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Sami
GivenName
Muhammad Ahsan
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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2021-04-01 14:46:38
AssociatedEntity
Name
Muhammad Ahsan Sami
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
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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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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windows xp
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2021-04-05T12:00:09
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2021-04-05T12:00:09
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