Abstract
A new scheme of data-driven segmentation is proposed, which is based on detection of object boundary, and volumetric pattern reconstruction as implicit function by using the detected object boundary and the radial basis functions (RBF). By using clinical X-ray CT data, applications in visualization of the pancreatic duct by MINIP of curved thin-slab and in liver segmentation are shown.
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© 2002 Springer-Verlag Berlin Heidelberg
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Masutani, Y. (2002). RBF-Based Representation of Volumetric Data: Application in Visualization and Segmentation. In: Dohi, T., Kikinis, R. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. MICCAI 2002. Lecture Notes in Computer Science, vol 2489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45787-9_38
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DOI: https://doi.org/10.1007/3-540-45787-9_38
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