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Computational methods for PDE constr...
~
Rensselaer Polytechnic Institute.
Computational methods for PDE constrained minimization problems in bio-mechanical imaging.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Computational methods for PDE constrained minimization problems in bio-mechanical imaging./
作者:
Tyagi, Mohit.
面頁冊數:
1 online resource (109 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
Contained By:
Dissertation Abstracts International78-02B(E).
標題:
Mechanical engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9781369136760
Computational methods for PDE constrained minimization problems in bio-mechanical imaging.
Tyagi, Mohit.
Computational methods for PDE constrained minimization problems in bio-mechanical imaging.
- 1 online resource (109 pages)
Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
Thesis (Ph.D.)
Includes bibliographical references
Disease changes the elastic properties of tissue. Further it is also affected by the elastic properties of tissue. Therefore measuring and quantifying the elastic properties of tissue can lead to techniques that are useful in the detection, diagnosis and treatment of different types of disease.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369136760Subjects--Topical Terms:
557493
Mechanical engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Computational methods for PDE constrained minimization problems in bio-mechanical imaging.
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Disease changes the elastic properties of tissue. Further it is also affected by the elastic properties of tissue. Therefore measuring and quantifying the elastic properties of tissue can lead to techniques that are useful in the detection, diagnosis and treatment of different types of disease.
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Elasticity imaging is a collection of techniques that are used to create images of mechanical properties of tissue. In elasticity imaging, the tissue is deformed, and the corresponding displacement field within the tissue is measured using standard imaging modalities such as ultrasound, optical coherence tomography, etc. Once the deformation field is obtained an inverse problem is solved in order to determine the spatial distribution of mechanical properties.
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This dissertation is focused on the solution of this inverse problem. In particular, we develop and implement techniques that can account for additional data (force and traction data, and three-dimensional data acquired on subjects) and techniques that are numerically more robust. The inclusion of force and traction data leads to quantitative elasticity imaging techniques that have been shown to improve the diagnostic capabilities of elasticity imaging. The application of elasticity imaging to three-dimensional clinical data leads to three-dimensional mechanical images of tumors that should be useful in surgical planning and training. Finally, the development of robust and stable finite element methods leads to numerical methods that can handle noise more effectively.
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Present work focuses on developing new formulations to account for different types of data for quasi-static elasticity imaging of breast tissue. In addition to this, we have made an effort to make the elasticity imaging more robust.
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