Automated analysis of human cochlea shape variability from segmented μ CT images

Abstract : The aim of this study is to define an automated and reproducible framework for cochlear anatomical analysis from high-resolution segmented images and to provide a comprehensive and objective shape variability study suitable for cochlear implant design and surgery planning. For the scala tympani (ST), the scala vestibuli (SV) and the whole cochlea, the variability of the arc lengths and the radial and longitudinal components of the lateral, central and modiolar paths are studied. The robustness of the automated cochlear coordinate system estimation is validated with synthetic and real data. Cochlear cross-sections are statistically analyzed using area, height and width measurements. The cross-section tilt angle is objectively measured and this data documents a significant feature for occurrence of surgical trauma.
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Thomas Demarcy, Clair Vandersteen, Nicolas Guevara, Charles Raffaelli, Dan Gnansia, et al.. Automated analysis of human cochlea shape variability from segmented μ CT images. Computerized Medical Imaging and Graphics, Elsevier, 2017, 59 (July 2017), pp.1 - 12. 〈http://www.sciencedirect.com/science/article/pii/S0895611117300332〉. 〈10.1016/j.compmedimag.2017.04.002〉. 〈hal-01528489〉

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