13 March 2018 Validation of cochlear implant electrode localization techniques
Author Affiliations +
Cochlear implants (CIs) are standard treatment for patients who experience sensorineural hearing loss. Although these devices have been remarkably successful at restoring hearing, it is rare to achieve natural fidelity, and many patients experience poor outcomes. Our group has developed image-guided CI programming techniques (IGCIP), in which image analysis techniques are used to locate the intra-cochlear position of CI electrodes to determine patient-customized settings for the CI processor. Clinical studies have shown that IGCIP leads to significantly improved outcomes. A crucial step is the localization of the electrodes, and rigorously quantifying the accuracy of our algorithms requires dedicated datasets. In this work, we discuss the creation of a ground truth dataset for electrode position and its use to evaluate the accuracy of our electrode localization techniques. Our final ground truth dataset includes 26 temporal bone specimens that were each implanted with one of four different types of electrode array by an experienced Otologist. The arrays were localized in conventional CT images using our automatic methods and manually in high resolution μCT images to create the ground truth. The conventional and μCT images were registered to facilitate comparison between automatic and ground truth electrode localization results. Our technique resulted in mean errors of 0.13mm in localizing the electrodes across 26 cases. Our approach successfully permitted characterizing the accuracy of our methods, which is critical to understand their limitations for use in IGCIP.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yiyuan Zhao, Yiyuan Zhao, Robert F. Labadie, Robert F. Labadie, Benoit M. Dawant, Benoit M. Dawant, Jack H. Noble, Jack H. Noble, "Validation of cochlear implant electrode localization techniques", Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761U (13 March 2018); doi: 10.1117/12.2293759; https://doi.org/10.1117/12.2293759

Back to Top