Tomographic imaging of time-varying distributions

Nathaniel P. Willis, Yoram Bresler

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


This paper addresses the tomographic imaging of time-varying distributions, when the temporal variation during acquisition of the data is high, precluding Nyquist rate sampling. This paper concentrates on the open (and hitherto unstudied) problem of nonperiodic temporal variation, which cannot be reduced to the time-invariant case by synchronous acquisition. The impact of the order of acquisition of different views on the L2 norm of the image-domain reconstruction error is determined for band-limited temporal variation. Based on this analysis, a novel technique for lowering the sampling rate requirement while preserving image quality is proposed and investigated. This technique involves an unconventional projection sampling order which is designed to minimize the L2 image-domain reconstruction error of a representative test image. A computationally efficient design procedure reduces the image data into a Grammian matrix which is independent of the sampling order. Further savings in the design procedure are realized by using a Zernike polynomial series representation for the test image. To illustrate the approach, reconstructions of a computer phantom using the best and conventional linear sampling orders are compared, showing a seven-fold decrease in the error norm by using the best scheme.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Number of pages13
ISBN (Print)0819402923, 9780819402929
StatePublished - 1990
EventBiomedical Image Processing - Santa Clara, CA, USA
Duration: Feb 12 1990Feb 13 1990

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherBiomedical Image Processing
CitySanta Clara, CA, USA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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