Automatic extraction of the mid-sagittal plane using an ICP variant

Lorenz Fieten; Jörg Eschweiler; Matías de la Fuente; Sascha Gravius; Klaus Radermacher

doi:10.1117/12.770472

17 March 2008 Automatic extraction of the mid-sagittal plane using an ICP variant

Lorenz Fieten, Jörg Eschweiler, Matías de la Fuente, Sascha Gravius, Klaus Radermacher

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69180L (2008) https://doi.org/10.1117/12.770472
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Precise knowledge of the mid-sagittal plane is important for the assessment and correction of several deformities. Furthermore, the mid-sagittal plane can be used for the definition of standardized coordinate systems such as pelvis or skull coordinate systems. A popular approach for mid-sagittal plane computation is based on the selection of anatomical landmarks located either directly on the plane or symmetrically to it. However, the manual selection of landmarks is a tedious, time-consuming and error-prone task, which requires great care. In order to overcome this drawback, previously it was suggested to use the iterative closest point (ICP) algorithm: After an initial mirroring of the data points on a default mirror plane, the mirrored data points should be registered iteratively to the model points using rigid transforms. Finally, a reflection transform approximating the cumulative transform could be extracted. In this work, we present an ICP variant for the iterative optimization of the reflection parameters. It is based on a closed-form solution to the least-squares problem of matching data points to model points using a reflection. In experiments on CT pelvis and skull datasets our method showed a better ability to match homologous areas.

Citation Download Citation

Lorenz Fieten, Jörg Eschweiler, Matías de la Fuente, Sascha Gravius, and Klaus Radermacher "Automatic extraction of the mid-sagittal plane using an ICP variant", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69180L (17 March 2008); https://doi.org/10.1117/12.770472

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