Auditory nerve fiber localization using a weakly supervised non-rigid registration U-Net

Hannah G. Mason; Ziteng Liu; Jack H. Noble

doi:10.1117/12.3008646

29 March 2024 Auditory nerve fiber localization using a weakly supervised non-rigid registration U-Net

Hannah G. Mason, Ziteng Liu, Jack H. Noble

Author Affiliations +

Proceedings Volume 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling; 129282C (2024) https://doi.org/10.1117/12.3008646
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Cochlear implants (CIs) are neural prosthetics that can improve hearing in patients with severe-to-profound hearing loss. CIs induce hearing sensation by stimulating auditory nerve fibers (ANFs) using an electrode array that is surgically implanted into the cochlea. After the device is implanted, an audiologist programs the CI processor to optimize hearing performance. However, without knowing which ANFs are being stimulated by each electrode, audiologists must rely solely on patient performance to inform the programming adjustments. Patient-specific neural stimulation modeling has been proposed to provide objective information to assist audiologists with programming, but this approach requires accurate localization of ANFs in patient CT images. In this paper, we propose an automatic neural-network-based method for atlas-based localization of the ANFs. Our results show that our method is able to produce smooth ANF predictions that are more realistic than those produced by a previously proposed semi-manual localization method. Accurate and realistic ANF localizations are critical for constructing patient-specific ANF stimulation models for model guided CI programming.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hannah G. Mason, Ziteng Liu, and Jack H. Noble "Auditory nerve fiber localization using a weakly supervised non-rigid registration U-Net", Proc. SPIE 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling, 129282C (29 March 2024); https://doi.org/10.1117/12.3008646

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