IEEE Transactions on Pattern Analysis and Machine Intelligence
CEASAR: a smooth, accurate and robust centerline extraction algorithm
Proceedings of the conference on Visualization '00
Model-Based Multiscale Detection of 3D Vessels
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Principal Flow for Tubular Objects with Non-Circular Cross-Sections
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Three-dimensional modeling and visualization of the cochlea on the Internet
IEEE Transactions on Information Technology in Biomedicine
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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.