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Abstract #3738

Semi-Automated 3D Cochlea Subregional Segmentation on T2-Weighted MRI Scans

William J Matloff1, Daniel J Matloff1, Arthur W Toga1, Taeuk Cheon2, Jangwook Gwak2, Yehree Kim2, Hong Ju Park2, and Hosung Kim1
1Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 2Department of Otorhinolaryngology-Head and Neck Surgery, Asan Medical Center, Seoul, Korea, Republic of

For MRI-based studies of cochlea-related diseases, segmenting the cochlea and modiolus is often essential for quantifying disease-related morphological and intensity changes. Methods for automatic 3D segmentation of these structures on MRI scans, however, are not well established. We aimed to develop a semi-automated, multi-atlas based approach to segmenting the cochlea and modiolus, distinguishing between the cochlear basal and mid-apical turns. We found this approach to have good agreement with manual segmentation, demonstrating its potential in quantitative analyses. Moreover, the definition of the three subregions had good validity, as indicated by the high inter-rater agreement in segmentation.

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