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3D landmark detection for augmented reality based otologic procedures

Abstract : Ear consists of the smallest bones in the human body and does not contain significant amount of distinct landmark points that may be used to register a preoperative CT-scan with the surgical video in an augmented reality framework. Learning based algorithms may be used to help the surgeons to identify landmark points. This paper presents a convolutional neural network approach to landmark detection in preoperative ear CT images and then discusses an augmented reality system that can be used to visualize the cochlear axis on an otologic surgical video.
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Contributor : Raabid Hussain <>
Submitted on : Sunday, September 1, 2019 - 6:20:19 PM
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  • HAL Id : hal-02275729, version 1


Raabid Hussain, Caroline Guigou, Kibrom Berihu Girum, Alain Lalande, Alexis Bozorg Grayeli. 3D landmark detection for augmented reality based otologic procedures. Surgetica, Jun 2019, Rennes, France. ⟨hal-02275729⟩



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