Maximum cross-entropy generalized series reconstruction

C. P. Hess, Zhi Pei Liang, P. C. Lauterbur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This article addresses the classical image reconstruction problem from limited Fourier data. In particular, we deal with the issue of how to incorporate constraints provided in the form of a high-resolution reference image which approximates the desired image. A new algorithm is described which represents the desired image using a family of basis functions derived from translated and rotated versions of the reference image. The selection of the most efficient basis function set from this family is guided by the principle of maximum cross-entropy. Simulation and experimental results have shown that the algorithm can achieve high resolution with a small number of data points while accounting for relative misregistration between the reference and measured data. The technique proves to be useful for a number of time-sequential magnetic resonance imaging applications, for which significant improvement in temporal resolution can be obtained, even as the object undergoes bulk motion during the acquisition.

Original languageEnglish (US)
Title of host publicationBiomedical Imaging V - Proceedings of the 5th IEEE EMBS International Summer School on Biomedical Imaging, SSBI 2002
EditorsJean-Louis Coatrieux, Christian Roux
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages258-265
Number of pages8
ISBN (Electronic)0780375076, 9780780375079
DOIs
StatePublished - 2002
Event5th IEEE EMBS International Summer School on Biomedical Imaging, SSBI 2002 - Berder Island, France
Duration: Jun 15 2002Jun 23 2002

Publication series

NameBiomedical Imaging V - Proceedings of the 5th IEEE EMBS International Summer School on Biomedical Imaging, SSBI 2002

Other

Other5th IEEE EMBS International Summer School on Biomedical Imaging, SSBI 2002
Country/TerritoryFrance
CityBerder Island
Period6/15/026/23/02

Keywords

  • generalized series
  • image representation
  • maximum cross-entropy

ASJC Scopus subject areas

  • Biotechnology
  • Radiology Nuclear Medicine and imaging

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