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Variable Scale Statistics For Cardiac Segmentation and Shape Analysis

Cois, Constantine Aaron (2008) Variable Scale Statistics For Cardiac Segmentation and Shape Analysis. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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A novel framework for medical image analysis, known as Shells and Spheres, has been developed by our research lab. This framework utilizes spherical operators of variable radius, centered at each image pixel and sized to reach, but not cross, the nearest boundary. Statistical population tests are performed on the populations of pixels within adjacent spheres to compare image regions across boundaries, delineating bothindependent image objects and the boundaries between them. This research has focused on developing the Shells and Spheres frameworkand applying it to the problem of segmentation of anatomical objects. Furthermore, we have rigorously studied the framework and its applications to clinical segmentation, validating and improving our n-dimensional segmentation algorithm. To this end, we have enhanced the original Shells and Spheres segmentation algorithm by adding a priori information, developing techniques for optimizing algorithm parameters, implementing a software platform for experimentation, and performing validation experiments using real 3D ovine cardiac MRI data. The system developed provides automated 3D segmentation given a priori information in the form of a trivial 2D manual training procedure, which involves tracing a single 2D contour from which 3D algorithm parameters are then automatically derived. We apply this system tosegmentation of the Right Ventricular Outflow Tract (RVOT) to aid in research toward the creation of a Tissue Engineered Pulmonary Valve(TEPV). Experimental methods are presented for the development and validation of the system, as well as a detailed description of the Shells and Spheres framework, our segmentation algorithm, and the clinical significance of this work.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Cois, Constantine
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairStetten, George
Committee MemberLi, C. Cccl@engr.pitt.eduCCL
Committee MemberBoston, J. Rboston@engr.pitt.eduBBN
Committee MemberChen,
Committee MemberSacks,
Date: 30 January 2008
Date Type: Completion
Defense Date: 12 October 2007
Approval Date: 30 January 2008
Submission Date: 26 October 2007
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Bioengineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Computer Vision; Image Analysis; Image Segmentation; Medical Image Analysis; Medical Imaging; Cardiovascular Imaging; Shape Modeling
Other ID:, etd-10262007-093528
Date Deposited: 10 Nov 2011 20:03
Last Modified: 15 Nov 2016 13:50


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