Abstract
This paper presents a series of 3D statistical models of the cortical sulci. They are built from points located automatically over the sulcal fissures, and corresponded automatically using variants on the Iterative Closest Point algorithm. The models are progressively improved by adding in more and more structural and configural information, and the final results are consistent with findings from other anatomical studies. The models can be used to locate and label anatomical features automatically in 3D head images for analysis, visualisation, classification, and normalisation.
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Caunce, A., Taylor, C.J. (1999). Using Local Geometry to Build 3D Sulcal Models. In: Kuba, A., Šáamal, M., Todd-Pokropek, A. (eds) Information Processing in Medical Imaging. IPMI 1999. Lecture Notes in Computer Science, vol 1613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48714-X_15
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DOI: https://doi.org/10.1007/3-540-48714-X_15
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