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Markerless Image-to-Patient Registration Using Stereo Vision : Comparison of Registration Accuracy by Feature Selection Method and Location of Stereo Bision System
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 Title & Authors
Markerless Image-to-Patient Registration Using Stereo Vision : Comparison of Registration Accuracy by Feature Selection Method and Location of Stereo Bision System
Joo, Subin; Mun, Joung-Hwan; Shin, Ki-Young;
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 Abstract
This study evaluates the performance of image to patient registration algorithm by using stereo vision and CT image for facial region surgical navigation. For the process of image to patient registration, feature extraction and 3D coordinate calculation are conducted, and then 3D CT image to 3D coordinate registration is conducted. Of the five combinations that can be generated by using three facial feature extraction methods and three registration methods on stereo vision image, this study evaluates the one with the highest registration accuracy. In addition, image to patient registration accuracy was compared by changing the facial rotation angle. As a result of the experiment, it turned out that when the facial rotation angle is within 20 degrees, registration using Active Appearance Model and Pseudo Inverse Matching has the highest accuracy, and when the facial rotation angle is over 20 degrees, registration using Speeded Up Robust Features and Iterative Closest Point has the highest accuracy. These results indicate that, Active Appearance Model and Pseudo Inverse Matching methods should be used in order to reduce registration error when the facial rotation angle is within 20 degrees, and Speeded Up Robust Features and Iterative Closest Point methods should be used when the facial rotation angle is over 20 degrees.
 Keywords
Surgical navigation;Stereo vision;Feature selection;Markerless registration;
 Language
Korean
 Cited by
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