The goals of this dissertation are to fully automate the image processing techniques needed in the post-operative stage of IGCIP and to perform a thorough analysis of (a) the robustness of the automatic image processing techniques used in IGCIP and (b) assess the sensitivity of the IGCIP process as a whole to individual components. The automatic methods that have been developed include the automatic localization of both closely- and distantly-spaced CI electrode arrays in post-implantation CTs and the automatic selection of electrode configurations based on the stimulation patterns. Together with the existing automatic techniques developed for IGCIP, the proposed automatic methods enable an end-to-end IGCIP process that takes pre- and post-implantation CT images as input and produces a patient-customized electrode configuration as output.
Cite
@article{arxiv.1909.10922,
title = {Automatic techniques for cochlear implant CT image analysis},
author = {Yiyuan Zhao},
journal= {arXiv preprint arXiv:1909.10922},
year = {2021}
}
Comments
This is a preprint of Yiyuan Zhao's Ph.D. dissertation from Vanderbilt University, Nashville, TN, USA. Trivial formatting modifications have been made in the arxiv version for readability. Vanderbilt University Electronic These & Dissertation (https://etd.library.vanderbilt.edu/) has the original submission on May 11 2018, and will be released on May 11 2020