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A Dynamic-Image Computational Approach for Modeling the Spine

Haque, Md. Abedul (2014) A Dynamic-Image Computational Approach for Modeling the Spine. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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We propose a dynamic-image driven computational approach for the modeling and simulation of the spine. We use static and dynamic medical images, computational methods and anatomic knowledge to accurately model and measure the subject-specific dynamic behavior of structures in the spine. The resulting models have applications in biomechanical simulations, computer animation, and orthopaedic surgery.

We first develop a semi-automated motion reconstruction method for measuring 3D motion with sub-millimeter accuracy. The automation of the method enables the study of subject-specific spine kinematics over large groups of population. The accuracy of the method enables the modeling and analysis of small anatomical features that are difficult to capture in-vivo using existing imaging techniques. We then develop a set of computational tools to model spine soft-tissue structures. We build dynamic-motion driven geometric models that combine the complementary strengths of the accurate but static models used in orthopaedics and the dynamic but low level-of-detail multibody simulations used in humanoid computer animation. Leveraging dynamic images and reconstructed motion, this approach allows the modeling and analysis anatomical features that are too small to be imaged in-vivo and of their dynamic behavior. Finally, we generate predictive, subject-specific models of healthy and symptomatic spines. The predictive models help to identify, understand and validate hypotheses about spine disorders.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Haque, Md.
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMarai, G. Elisabetamarai@cs.pitt.eduMARAI
Committee MemberHauskrecht, Milosmilos@cs.pitt.eduMILOS
Committee MemberWang, Jingtaojingtaow@cs.pitt.eduJINGTAOW
Committee MemberPolard,
Date: 29 May 2014
Date Type: Publication
Defense Date: 7 April 2014
Approval Date: 29 May 2014
Submission Date: 8 April 2014
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 115
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Geometric Modeling, Medical Imaging, Spine Soft-tissue Modeling, Motion Reconstruction, Anatomical Joint Modeling and Simulation
Date Deposited: 29 May 2014 14:15
Last Modified: 19 Dec 2016 14:41


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