Sensitivity of intra-cochlear anatomy segmentation methods to varying image acquisition parameters

Mohammad M. R. Khan; Rueben Banalagay; Robert F. Labadie; Jack H. Noble

doi:10.1117/12.2611684

4 April 2022 Sensitivity of intra-cochlear anatomy segmentation methods to varying image acquisition parameters

Mohammad M. R. Khan, Rueben Banalagay, Robert F. Labadie, Jack H. Noble

Author Affiliations +

Proceedings Volume 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling; 120340I (2022) https://doi.org/10.1117/12.2611684
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

During cochlear implant (CI) surgical procedures, the surgeon inserts an electrode array into the patient’s cochlea to restore hearing sensation through auditory nerve stimulation. Due to the significant variability in cochlear anatomy from person to person, patient-customized CI surgery planning has the potential to improve the outcome of the CI procedure. For presurgery planning, accurate segmentation of intra-cochlear structures is essential. In this work, we investigate the performance of intra-cochlear segmentation algorithms as a function of variations in image acquisition parameters (i.e., resolution, blurring effect and noise level) that exist in clinical CT images. A dataset of preoperative μCT images of 11 cadaveric temporal bone specimens was used to generate 110 synthetic pseudo-CT images with varying resolution and filter parameters. An active shape model (ASM) based method was evaluated to segment the intra-cochlear structures in those pseudo-CT images. Our results show that the volume of the segmented structures is significantly and strongly correlated with both the resolution and the reconstruction filter strength of the synthetic pseudo-CT images. Recognizing this bias is important for clinicians who use these segmentations or take manual measurements of the cochlea from CT images for pre-surgical planning of CI procedures.

Conference Presentation

Citation Download Citation

Mohammad M. R. Khan, Rueben Banalagay, Robert F. Labadie, and Jack H. Noble "Sensitivity of intra-cochlear anatomy segmentation methods to varying image acquisition parameters", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 120340I (4 April 2022); https://doi.org/10.1117/12.2611684

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