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A computerized image analysis framework for dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with applications to breast cancer
Descriptive
TitleInfo
Title
A computerized image analysis framework for dynamic
contrast enhanced magnetic resonance imaging
(DCE-MRI) with applications to breast cancer
contrast enhanced magnetic resonance imaging
(DCE-MRI) with applications to breast cancer
Name
(type = personal)
NamePart
(type = family)
Agner
NamePart
(type = given)
Shannon Christine
NamePart
(type = date)
1980-
DisplayForm
Shannon Agner
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(authority = RULIB)
author
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(type = personal)
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(type = family)
Madabhushi
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(type = given)
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Anant Madabhushi
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Advisory Committee
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(authority = RULIB)
chair
Name
(type = personal)
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(type = family)
Ganesan
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(type = given)
Shridar
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Shridar Ganesan
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
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(type = family)
Cai
NamePart
(type = given)
Li
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Li Cai
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
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(type = family)
Rosen
NamePart
(type = given)
Mark A
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Mark A Rosen
Affiliation
Advisory Committee
Role
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(authority = RULIB)
outside member
Name
(type = personal)
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(type = family)
Feldman
NamePart
(type = given)
Michael D
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Michael D Feldman
Affiliation
Advisory Committee
Role
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(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2011
DateOther
(qualifier = exact);
(type = degree)
2011-05
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Subject
(authority = RUETD)
Topic
Biomedical Engineering
Subject
(authority = ETD-LCSH)
Topic
Breast--Magnetic resonance imaging
Subject
(authority = ETD-LCSH)
Topic
Breast--Cancer--Magnetic resonance imaging
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
(type = local)
rucore19991600001
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Shannon Christine Agner
PhysicalDescription
Form
(authority = gmd)
electronic resource
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application/pdf
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text/xml
Extent
xix, 107 p. : ill.
Abstract
(type = abstract)
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides a wealth of information about the anatomy of the breast, particularly in the setting of breast cancer diagnosis. In addition to the images it provides regarding the architecture of
breast tissue, it also provides functional information about blood flow by means of the DCE study. The sensitivity of DCE-MRI has been reported at close to 100%, so the difficult tasks for the radiologist in reviewing breast DCE-MRI are: (1) discerning
between which lesions are benign and which are malignant; and (2) doing so for a patient study that involves hundreds of images and is 4-dimensional. Because of the great detail and volume of information DCE-MRI provides, computational methods for both extracting and analyzing information derived from the images are useful in distilling the entire patient study down to the most salient images and features for the
radiologist to examine. In this dissertation, computer-based methods developed for
analyzing the data acquired in a breast DCE-MRI patient study are described. In the first part, pre-processing methods used for aligning the images of the timedependent DCE study are explained. Because segmentation is important for describing the morphology of the lesion as well as the region of interest for any subsequent quantitative analysis of a lesion, as a second step to pre-processing, a spectral embedding based active contour (SEAC) method for segmentation of lesions is developed and tested. A
feature developed for extracting the spatiotemporal characteristics of breast lesions, termed textural kinetics, is then described, and its utility is demonstrated for distinguishing benign from malignant lesions as well as in identifying triple negative breast
lesions, a lesion type that is extremely aggressive and has no targeted therapies. Finally, these quantitative methods are summarized in a computer aided diagnosis framework that provides insight into the biologic nature of breast lesion subtypes as well as for
directing treatment and determining prognosis.
breast tissue, it also provides functional information about blood flow by means of the DCE study. The sensitivity of DCE-MRI has been reported at close to 100%, so the difficult tasks for the radiologist in reviewing breast DCE-MRI are: (1) discerning
between which lesions are benign and which are malignant; and (2) doing so for a patient study that involves hundreds of images and is 4-dimensional. Because of the great detail and volume of information DCE-MRI provides, computational methods for both extracting and analyzing information derived from the images are useful in distilling the entire patient study down to the most salient images and features for the
radiologist to examine. In this dissertation, computer-based methods developed for
analyzing the data acquired in a breast DCE-MRI patient study are described. In the first part, pre-processing methods used for aligning the images of the timedependent DCE study are explained. Because segmentation is important for describing the morphology of the lesion as well as the region of interest for any subsequent quantitative analysis of a lesion, as a second step to pre-processing, a spectral embedding based active contour (SEAC) method for segmentation of lesions is developed and tested. A
feature developed for extracting the spatiotemporal characteristics of breast lesions, termed textural kinetics, is then described, and its utility is demonstrated for distinguishing benign from malignant lesions as well as in identifying triple negative breast
lesions, a lesion type that is extremely aggressive and has no targeted therapies. Finally, these quantitative methods are summarized in a computer aided diagnosis framework that provides insight into the biologic nature of breast lesion subtypes as well as for
directing treatment and determining prognosis.
Identifier
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http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000060977
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NjNbRU
Identifier
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doi:10.7282/T3KK9B4K
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
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The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Agner
GivenName
Shannon
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2011-04-15 16:33:40
AssociatedEntity
Name
Shannon Agner
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)
2011-05-31
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = end)
2011-11-30
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after November 30th, 2011.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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