Abstract
We introduce a new approach for the localization of 3D anatomical point landmarks based on 3D parametric intensity models which are directly fit to an image. We propose different analytic intensity models based on the Gaussian error function in conjunction with 3D rigid transformations as well as deformations to efficiently model tip-like, saddle-like, and sphere-like structures. The approach has been successfully applied to accurately localize anatomical landmarks in 3D MR and 3D CT image data. We have also compared the experimental results with the results of a previously proposed 3D differential operator. It turns out that the new approach significantly improves the localization accuracy.
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Wörz, S., Rohr, K. (2003). 3D Parametric Intensity Models for the Localization of Different Types of 3D Anatomical Point Landmarks in Tomographic Images. In: Michaelis, B., Krell, G. (eds) Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, vol 2781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45243-0_29
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DOI: https://doi.org/10.1007/978-3-540-45243-0_29
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