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Cone-Beam Image Reconstruction by Moving Frames

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Book cover Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis (MMBIA 2004, CVAMIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3117))

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Abstract

In this paper, we present a new algorithmic paradigm for cone-beam image reconstruction. The new class of algorithms, referred to as cone-beam reconstruction by moving frames, enables numerical implementation of exact cone-beam inversion using its intrinsic geometry. In particular, our algorithm allows a 3-D discrete approach to the differentiation-backprojection operator on the curved manifolds appearing in all analytical cone-beam inverse formulations. The enabling technique, called the method of moving frames, has been popular in the computer vision community for many years [3]. Although cone-beam image reconstruction has come from a different origin and has been until now developed along very different lines from computer vision algorithms, we can find analogies in their line-and-plane geometry. We demonstrate how the moving frame technique can be made into a ubiquitous and powerful computational tool for designing and implementing more robust and more accurate cone-beam reconstruction algorithms.

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Author information

Authors and Affiliations

  1. Biovisum, Inc., Boston, MA, 02116, USA

    Xiaochun Yang

  2. MIT EECS and CSAIL, Cambridge, MA, 02139, USA

    Berthold K. P. Horn

Authors
  1. Xiaochun Yang
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  2. Berthold K. P. Horn
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Iowa, 52242, Iowa City, IA, USA

    Milan Sonka

  2. Computational Biomedicine Lab, University of Houston, Houston, TX

    Ioannis A. Kakadiaris

  3. Center for Machine Perception, Czech Technical University, 121 35, Prague 2, Czech Republic

    Jan Kybic

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© 2004 Springer-Verlag Berlin Heidelberg

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Yang, X., Horn, B.K.P. (2004). Cone-Beam Image Reconstruction by Moving Frames. In: Sonka, M., Kakadiaris, I.A., Kybic, J. (eds) Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis. MMBIA CVAMIA 2004 2004. Lecture Notes in Computer Science, vol 3117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27816-0_4

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  • DOI: https://doi.org/10.1007/978-3-540-27816-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22675-8

  • Online ISBN: 978-3-540-27816-0

  • eBook Packages: Springer Book Archive

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