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Pauly, O. ; Katouzian, A.* ; Eslami, A. ; Fallavollita, P.* ; Navab, N.*

Supervised classification for customized intraoperative augmented reality visualization.

In: 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (11th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2012, Atlanta, United States, 05. - 08. November 2012). Piscataway, NJ: IEEE, 2012. 311-312
DOI
In this paper, we present a fusion algorithm supplemented with appropriate visualization by selecting relevant information from different modalities in mixed and augmented reality (AR). This encompasses a learning based method upon relevance of information, defined by an expert, which ultimately enables confident interventional decisions based on mixed reality (MR) images. The performance of our developed fusion and tailored visualization techniques was evaluated by employing X-ray/optical images during surgery and validated qualitatively using a 5-point Likert scale. Our observations indicated that the proposed technique provided semantic contextual information about underlying pixels and in general was preferred over the traditional pixel-wise linear alpha-blending method.
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Publication type Article: Conference contribution
Editors Institute of Electrical and Electronics Engineers*
Corresponding Author
Keywords Camc ; Fusion ; Medical Augmented Reality ; Relevant Information ; Visualization ; X-ray
ISBN 978-146734660-3
Conference Title 11th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2012, Atlanta, United States, 05. - 08. November 2012
Proceedings Title 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Quellenangaben Volume: , Issue: , Pages: 311-312 Article Number: , Supplement: ,
Publisher IEEE
Publishing Place Piscataway, NJ
Non-patent literature Publications
Institute(s) Institute of Computational Biology (ICB)