Skip to main content

Reconstruction from Slow Rotation Dynamic SPECT Using a Factor Model

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1613))

Abstract

Slow rotation acquisition of dynamic data has several advantages over fast rotation acquisition which is currently the method of choice used for the acquisition of dynamic data in SPECT. Slow rotation is currently not used because of error from inconsistent data. In this work, we develop a method of reconstructing from projections that are inconsistent in time due to being acquired during a slow acquisition. Our method is based on a factor model of physiological data. A series of dynamic images are reconstructed, where each reconstructed image corresponds in time to only one projection. Such an under-determined reconstruction is shown to be possible through utilization of a factor model. Computer simulations are performed using simple phantoms. We found that we are able to accurately reconstruct the dynamic sequence for simple phantoms with temporal behavior corresponding to teboroxime-Tc-99m heart imaging.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chiao, P. C., Rogers. W. L., Clinthorne, N. H., Fessler, J. A., Hero, A. O.: Model-based estimation with boundary side information or boundary regularization. IEEE Trans. Med. Imag. 13 (1994) 227–234

    Article  Google Scholar 

  2. Matthews, J., Bailey, D., Cunningham, V.: The direct calculation of parametric images from dynamic PET data using maximum-likelihood iterative reconstruction. Phys. Med. Biol. 42 (1997) 1155–1173

    Article  Google Scholar 

  3. Zeng, G. L., Gullberg, G. T., Huesman, R. H.: Using linear time-invariant system theory to estimate kinetic parameters directly from projection measurements. IEEE Trans. Nuc. Sci. 42 (1995) 2339–2346

    Article  Google Scholar 

  4. Limber, M. N., Celler, A., Barney, J. S., Limber, M. A., Borwein, J. M.: Direct reconstruction of functional parameters for dynamic SPECT. IEEE Trans. Nuc. Sci. 42 (1995) 1249–1256

    Article  Google Scholar 

  5. Sitek, A., DiBella, E. V. R., Gullberg, G. T.: Direct extraction of tomographic time activity curves from dynamic SPECT projections using factor analysis. J. Nucl. Med. 39 (1998) 144P

    Google Scholar 

  6. Wu. H-M., Hoh, C. K., Choi, Y., Schelbert, H. R., Hawkins, R. A., Phelps, M. E., Huang, S-C.: Factor analysis for extraction of blood time-activity curves in dynamic FDG-PET studies. J. Nucl. Med. 36 (1995) 1714–1722

    Google Scholar 

  7. Coxson, P. G., Salmeron, E. M., Huesman, R. H., Mazoyer, B. M.: Simulation of compartmental models for kinetic data from a positron emission tomograph. Comput. Methods. Programs. Biomed. 37 (1992) 205–214

    Article  Google Scholar 

  8. Huesman, R. H., Mazoyer, B. M.: Kinetic data analysis with a noisy input function. Phys. Med. Biol. 32 (1987) 1569–1579

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sitek, A., Di Bella, E.V.R., Gullberg, G.T. (1999). Reconstruction from Slow Rotation Dynamic SPECT Using a Factor Model. In: Kuba, A., Šáamal, M., Todd-Pokropek, A. (eds) Information Processing in Medical Imaging. IPMI 1999. Lecture Notes in Computer Science, vol 1613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48714-X_42

Download citation

  • DOI: https://doi.org/10.1007/3-540-48714-X_42

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66167-2

  • Online ISBN: 978-3-540-48714-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics