The correlation between the stiffness and health of tissue is an accepted form of organ disease assessment. As a result, there has been a significant amount of interest in developing methods to image elasticity parameters (i.e. elastography). This work presents a technique that frames the elastography imaging problem within a non-rigid iterative registration approach. Through the use of finite element modeling and image comparison methods, material properties are varied in order to optimize the registration between a post-compressed image and a model-generated compressed image. The results shown here demonstrate the strong connection between image similarity and appropriate tissue parameters and the algorithm's ability to detect contrast in tissue stiffness. Simulations demonstrate that the method is effective over a wide range of scenarios. Also, we were successfully able to localize regions of stiffness within phantom data taken in both CT and MRI. By casting elasticity image reconstruction within the context of image similarity, the method is generalized to all forms of medical imaging.
Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-07212003-170400 |
Date | 21 July 2003 |
Creators | Washington, Chad Wayne |
Contributors | Michael I. Miga, Rober J. Roselli |
Publisher | VANDERBILT |
Source Sets | Vanderbilt University Theses |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.library.vanderbilt.edu/available/etd-07212003-170400/ |
Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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