Abstract
The cochlear ear implant has become a standard clinical intervention for the treatment of profound sensorineural hearing loss. After 20 years of research into implant design, there are still many unanswered clinical questions that could benefit from new analysis and modelling techniques. This research aims to develop techniques for extracting the cochlea from medical images to support clinical outcomes. We survey the challenges posed by some of these clinical questions and the problems of cochlea modeling. We present a novel algorithm for extracting tubular objects with non-circular cross-sections from medical images, including results from generated and clinical data. We also describe a cochlea model, driven by clinical knowledge and requirements, for representation and analysis. The 3-dimensional cochlea representation described herein is the first to explicitly integrate path and cross-sectional shape, specifically directed at addressing clinical outcomes. The tubular extraction algorithm described is one of very few approaches capable of handling non-circular cross-sections. The clinical results, taken from a human CT scan, show the first extracted centreline path and orthogonal cross-sections for the human cochlea.
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References
Mondini, C.: Anatomia surdi nati sectio: Bononiensi scientiarum et artium instituto atque academia commentarii. Bononiae 7(1791), 419–431
The Bionic Ear Institute, Melbourne, Australia: About the bionic ear (2004), http://www.bionicear.org/bei/AboutHistory.html
Loizou, P.: Introduction to cochlear implants. IEEE Engineering in Medicine and Biology, 32–42 (1999)
Whiting, B., Bae, K., Skinner, M.: Cochlear implants: Three-dimensional localisation by means of coregistration of CT and conventional radiographs. Radiology 221, 543–549 (2001)
Yoo, S., Rubinstein, J., Vannier, M.: Three-dimensional geometric modeling of the cochlea using helico-spiral approximation. IEEE Transactions on Biomedical Engineering 47, 1392–1402 (2000)
Ketten, D., Skinner, M., Wang, G., Vannier, M., Gates, G., Neely, G.: In vivo measures of cochlear length and insertion depth of nucleus cochlea implant electrode arrays. Ann. Otol., Rhinol. Laryngol. 107, 515–522 (1989)
Cohen, L., Xu, J., Xu, S., Clark, G.: Improved and simplified methods for specifying positions of the electrode bands of a cochlear implant array. American Journal of Otology (1996)
Yoo, S., Wang, G., Rubenstein, J., Skinner, M., Vannier, M.: Three-dimensional modeling and visualisation of the cochlea on the internet. IEEE Transactions on Information Technology in Biomedicine 4, 144–151 (2000)
Wang, G., Vannier, M., Skinner, M., Kalender, W., Polacin, A., Ketten, D.: Unwrapping cochlear implants by spiral CT. IEEE Transactions on Biomedical Engineering 43, 891–900 (1996)
Aylward, S., Bullitt, E.: Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE Transactions on Medical Imaging 21, 61–75 (2002)
Frangi, A., Niessen, W., Hoogeveen, R., van Walsum, T., Viergever, M.: Model-based quantitation of 3-D magnetic resonance angiographic images. IEEE Transactions on Medical Imaging 18, 946–956 (1999)
Lorigo, L.M., Faugeras, O.D., Grimson, W.E.L., Keriven, R., Kikinis, R., Nabavi, A., Westin, C.F.: CURVES: Curve evolution for vessel segmentation. Medical Image Analysis 5, 195–206 (2001)
Yim, P., Cebral, J., Mullick, R., Marcos, H., Choyke, P.: Vessel surface reconstruction with a tubular deformable model. IEEE Transactions on Medical Imaging 20, 1411–1421 (2001)
Krissian, K., Vaillant, G.M.R., Trousset, Y., Ayache, N.: Model-based multiscale detection of 3D vessels. In: Computer Vision and Pattern Recognition, pp. 722–727. IEEE, Los Alamitos (1998)
Binford, T.: Visual perception by computer. In: IEEE Conference on Systems Science and Cybernetics (1971)
Zerroug, M., Nevatia, R.: Three-dimensional descriptions based on the analysis of the invariant and quasi-invariant properties of some curved-axis generalized cylinders. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 237–253 (1996)
Bitter, I., Sato, M., Bender, M., McDonnell, K.T., Kaufman, A., Wan, M.: CEASAR: a smooth, accurate and robust centerline extraction algorithm. In: Proceedings of the conference on Visualization 2000, pp. 45–52. IEEE Computer Society Press, Los Alamitos (2000)
Flasque, N., Desvignes, M., Constans, J.-M., Revenu, M.: Acquisition, segmentation and tracking of the cerebral vascular tree on 3D magnetic resonance angiography images. Medical Image Analysis 5, 173–183 (2001)
Baker, G., Barnes, N.: Principal flow for tubular objects with non-circular cross-sections. In: Proceedings of the International Conference on Pattern Recognition, Cambridge, England (2004)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–395 (1981)
Ibáñez, L., Schroeder, W., Ng, L., Cates, J.: 1. In: The ITK Software Guide, Kitware Inc (2003)
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Baker, G., O’Leary, S., Barnes, N., Kazmierczak, E. (2004). Cochlea Modelling: Clinical Challenges and Tubular Extraction. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_7
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DOI: https://doi.org/10.1007/978-3-540-30549-1_7
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