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Proceedings Paper

Evaluation of non-rigid registration parameters for atlas-based segmentation of CT images of human cochlea
Author(s): Mai Elfarnawany; S. Riyahi Alam; Sumit K. Agrawal; Hanif M. Ladak
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Paper Abstract

Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient’s hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828±0.021 and 0.25±0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.

Paper Details

Date Published: 24 February 2017
PDF: 7 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101330Z (24 February 2017); doi: 10.1117/12.2254040
Show Author Affiliations
Mai Elfarnawany, Western Univ. (Canada)
S. Riyahi Alam, Western Univ. (Canada)
Sumit K. Agrawal, Western Univ. (Canada)
Hanif M. Ladak, Western Univ. (Canada)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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