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Automatic G1 Surface Reconstruction from Serial Cross-Sectional Images

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Visual Information Systems. Web-Based Visual Information Search and Management (VISUAL 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5188))

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Abstract

Biomedical imaging facilities today like MRI, PET, CT scan and confocal microscopy produce sequentially parallel cross sectional images. Recon-structing trustworthy 3D explicit models which enable better understanding of the topology and shape of structure is crucial in facilitating diagnosis, improves surgical planning and aid in biological research.

Our technique produce a surface from G1 cross sectional contour curves of images. Surface accuracy is controlled by a tolerance measure. Features can be isolated and identified for corresspondence.

First the boundaries of the region of interest are extracted and corner points detected. G1 rational Bezier cubics, iteratively determined, are fitted piecewise between these corners and approximating the boundary. as close as need be. Adjacent contour curves are blended together to form the surface. Technique is fully automatic.

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Monica Sebillo Giuliana Vitiello Gerald Schaefer

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© 2008 Springer-Verlag Berlin Heidelberg

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Yahya, F., Md Ali, J., Abdul Majid, A., Ibrahim, A. (2008). Automatic G1 Surface Reconstruction from Serial Cross-Sectional Images. In: Sebillo, M., Vitiello, G., Schaefer, G. (eds) Visual Information Systems. Web-Based Visual Information Search and Management. VISUAL 2008. Lecture Notes in Computer Science, vol 5188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85891-1_12

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  • DOI: https://doi.org/10.1007/978-3-540-85891-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85890-4

  • Online ISBN: 978-3-540-85891-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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