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Automated and computationally efficient joint motion analysis using low quality fluoroscopy images

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TitleInfo
Title
Automated and computationally efficient joint motion analysis using low quality fluoroscopy images
Name (type = personal)
NamePart (type = family)
Ghafurian
NamePart (type = given)
Soheil
NamePart (type = date)
1982-
DisplayForm
Soheil Ghafurian
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Li
NamePart (type = given)
Kang
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Kang Li
Affiliation
Advisory Committee
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chair
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NamePart (type = family)
Albin
NamePart (type = given)
Susan
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Susan Albin
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Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Jeong
NamePart (type = given)
Myong K.
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Myong K. Jeong
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Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Hacihaliloglu
NamePart (type = given)
Ilker
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Ilker Hacihaliloglu
Affiliation
Advisory Committee
Role
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outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
DateOther (qualifier = exact); (type = degree)
2017-01
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2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The kinematic analysis of joint motion has proven to significantly improve orthopedic surgeries by enhancing surgery assessment, prosthesis design, and pathology diagnosis. This analysis is usually performed by a three to two dimensional (3D/2D) registration of the 3D bone model to a 2D radiographic video from C-arm fluoroscopy imaging machines. However, the practicality of such analysis is undermined due to lengthy and user-dependent 3D/2D image registration algorithms and the high cost of C-arm fluoroscopy imaging machines. Mini C-arm fluoroscopic machines are a more affordable alternative, but the low quality of their images has hindered their use in this application. In this thesis, we propose a novel 3D/2D image registration algorithm for the kinematic analysis of joint bones using mini C-arm fluoroscopy machines with significantly improved speed, despite their low quality images. This method performs a fast registration through a novel algorithm for quick and high-quality generation of digitally reconstructed radiographs (DRR), which is the bottleneck in such processes. Moreover, the dependency of the results on the user has been reduced as a new feature-based registration algorithm replaced the previously manual initialization phase of the process. This algorithm is able to reach the true registration from within 90 degrees of it, which is a substantial improvement over the existing methods. In addition, our algorithm performs the registration in significantly reduced time due to a smaller number of generated DRRs.
Subject (authority = RUETD)
Topic
Industrial and Systems Engineering
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_7867
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xviii, 85 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Joints--Physiology
Subject (authority = ETD-LCSH)
Topic
Fluoroscopy
Note (type = statement of responsibility)
by Soheil Ghafurian
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3S46VDM
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Ghafurian
GivenName
Soheil
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-01-13 11:31:56
AssociatedEntity
Name
Soheil Ghafurian
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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2017-01-13T16:25:11
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2017-01-13T16:25:11
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