Metal Artifact Reduction, Intra Cochlear Anatomy Segmentation, and Cochlear Implant Electrodes Localization in CT Images with a Multi- task 3D Network

摘要

Cochlear implants (CIs) are surgically implanted neural prosthetic devices to treat severe-to-profound hearing loss. Accurately localizing the CI electrodes relative to the intracochlear anatomy structures (ICAS) in the post-implantation CT (Post-CT) images of the CI recipients can help audiologists with the post-programming of the CIs. Localizing the electrodes and segmenting the ICAS in the Post-CT images are challenging due to the limited image resolution and the strong artifacts produced by the metallic electrodes. Currently, the most accurate approach to determine the physical relationship between the electrodes and the ICAS is to localize the electrodes in the Post-CT image, segment the ICAS in the pre-implantation CT (Pre-CT) image of the CI recipient, and register the two images. Here we propose a 3D multi-task network to remove the artifacts, segment the ICAS, and localize the electrodes in the Post-CT images simultaneously. Our network is trained with a small image set and achieves comparable segmentation results and encouraging electrode localization results compared to the current state-of-the-art methods. As our method does not require the Pre-CT images, it provides the audiologist with information that guides the programming process even for patients for whom these images are not available.