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Title page for ETD etd-04132011-145959


Type of Document Dissertation
Author Noble, Jack Henry
Author's Email Address jack.h.noble@vanderbilt.edu
URN etd-04132011-145959
Title Automatic Identification of the Structures of the Ear and a New Approach for Tubular Structure Modeling and Segmentation
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Benoit M. Dawant Committee Chair
Bennett A. Landman Committee Member
Don M. Wilkes Committee Member
J. Michael Fitzpatrick Committee Member
Robert F. Labadie Committee Member
Keywords
  • Dijkstra's algorithm
  • model-based segmentation
  • atlas-based segmentation
  • optimal path
  • temporal bone
  • tubular segmentation
Date of Defense 2011-03-30
Availability unrestricted
Abstract
This dissertation presents studies on, and from, the development of algorithms for the automatic segmentation of the structures of the ear. Many otological procedures would benefit from a system that automatically identifies anatomical structures of the ear in CT. Conventional (registration-based) segmentation techniques are suitable for identifying ear structures that have high intensity contrast in CT or those for which a high degree of accuracy is not necessary. For some ear structures, conventional techniques are inadequate, and other segmentation methods must be used or developed.

In this dissertation, approaches that permit the automatic identification of ear structures will be presented. This will include the ossicles, external auditory canal, cochlea, scala tympani, scala vestibuli, facial nerve, chorda tympani, semicircular canals, and the carotid artery. Each of these sensitive structures lies within millimeters of the surgical approach for various types of procedures.

Out of the above mentioned structures, six distinct tubular shaped structures are represented, each of which has unique properties that make detection difficult. This has led to the development of an algorithm for the segmentation of general tubular structures, which is also presented in this dissertation. This algorithm is validated on these ear structures as well as other tubular structures outside of the ear.

The results of all methods presented in this work are analyzed, and quantitatively compared to expert drawn or expert edited segmentations, which are treated as the gold standard.

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