A temporal interpolation approach for dynamic reconstruction in perfusion CT

Medical Physics

Volumn 34, Issue 7, 2007, Pages 3077-3092

  Montes, Pau ^a   Lauritsch, Günter ^b  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; BIOMEDICAL SIGNAL PROCESSING; INTERPOLATION; POLYNOMIAL APPROXIMATION; SCANNING;

ATTENUATION COEFFICIENT; COMPUTATIONAL COSTS; DYNAMIC RECONSTRUCTION; DYNAMIC RECONSTRUCTION ALGORITHMS; LINEAR INTERPOLATION; SIMULATION STUDIES; TEMPORAL INTERPOLATION; TEMPORAL RESOLUTION;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; COMPUTED TOMOGRAPHY SCANNER; COMPUTER ASSISTED TOMOGRAPHY; IMAGE QUALITY; IMAGE RECONSTRUCTION; INTERMETHOD COMPARISON; LINEAR REGRESSION ANALYSIS; OPTICAL RESOLUTION; PERFUSION; PRIORITY JOURNAL; RADIATION EXPOSURE; ROTATION; SIGNAL PROCESSING; SIMULATION; THEORETICAL STUDY; VELOCITY; X RAY; HUMAN; IMAGING PHANTOM; SCINTIGRAPHY;

ALGORITHMS; HUMANS; PERFUSION IMAGING; PHANTOMS, IMAGING; TOMOGRAPHY, X-RAY COMPUTED;

EID: 34347368724     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.2746486     Document Type: Article

References (21)

1. M. Wiesmann, G. Bohner, and R. Klingebiel, " Zerebrale Perfusionsbildgebung mittels Mehrschichtspiral-CT., " Klinische Neuroradiologie 13, 92-107 (2004).
2. M. Wintermark, M. Reichhart, O. Cuisenaire, P. Maeder, J. P. Thiran, P. Schnyder, J. Bogousslavsky, and R. Meuli, " Comparison of admission perfusion computed tomography and qualitative diffusion- and perfusion-weighted magnetic resonance imaging in acute stroke patients., " Stroke 33, 2025-2031 (2002).
3. P. Schramm, P. D. Schellinger, E. Klotz, K. Kallenberg, J. B. Fiebach, S. Külkens, S. Heiland, M. Knauth, and K. Sartor, " Comparison of perfusion Computed Tomography and Computed Tomography Angiography source images with perfusion-weighted imaging and diffusion-weighted imaging in patients with acute stroke of less than 6 hours' duration., " Stroke 35, 1652-1658 (2004).
4. E. Klotz and M. König, " Perfusion measurements of the brain: Using dynamic CT for the quantitative assessment of cerebral ischemia in acute stroke., " Eur. J. Radiol. 30, 170-184 (1999).
5. K. Miles, P. Dawson, and M. Blomley, Functional Computed Tomography (Isis Medical Media, 1997).
6. K. A. Miles and M. R. Griffiths, " Perfusion CT: A worthwile enhancement?, " Br. J. Radiol. 76, 220-231 (2003).
7. K. Taguchi, " Temporal resolution and the evaluation of candidate algorithms for four dimensional CT., " Med. Phys. 30, 640-650 (2003).
8. M. D. Silver, " A method for including redundant data in computed tomography., " Med. Phys. 27, 773-774 (2000).
9. L. A. Feldkamp, L. C. Davis, and J. W. Kress, " Practical cone-beam algorithm., " J. Opt. Soc. Am. 1, 612-619 (1984).
10. D. L. Parker, " Optimal short-scan convolution reconstruction for fan-beam CT., " Med. Phys. 9, 254-257 (1982).
11. J. Hsieh, Y. Wei, and G. Wang, " Fractional scan algorithms for low-dose perfusion CT., " Med. Phys. 31, 1254-1257 (2004).
12. P. Grangeat, A. Koenig, T. Rodet, and S. Bonnet, " Theoretical framework for a dynamic cone-beam reconstruction algorithm based on a dynamic particle model., " Phys. Med. Biol. 47, 2611-2625 (2002).
13. M. Grass, T. Köhler, and R. Proksa, " 3D cone-beam CT reconstruction for circular trajectories., " Phys. Med. Biol. 45, 329-347 (2000).
14. A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing (Prentice Hall, 1998).
15. M. Unser, " Splines. A perfect fit for signal and image processing., " IEEE Signal Process. Mag. 16, 22-38 (1999).
16. A. Aldroubi, M. Unser, and M. Eden, " Cardinal spline filters: Stability and convergence to the ideal sinc interpolator., " Signal Process. 28, 127-138 (1992).
17. M. Unser, A. Aldroubi, and M. Eden, " B-spline signal processing: Part II-efficient design and applications., " IEEE Trans. Signal Process. 41, 834-848 (1993).
18. S. Schaller, " Practical image reconstruction for cone-beam computed tomography., " Ph.D. thesis, Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany, 1998.
19. S. Bonnet, A. Koenig, P. Hugonnard, and P. Grangeat, " Time delay analysis in online 4-D CT., " in Fully 3D Image Reconstruction Meeting in Radiology and Nuclear Medicine (Saint Malo, France, 2003).
20. P. Montes, Dynamic cone-beam reconstruction for perfusion computed tomography., Ph.D. thesis, Interdisciplinary Center for Scientific Computing, Ruprecht-Karls-Universität Heidelberg, Germany, 2006, http://www.ub.uni- heidelberg.de/archiv/7020/
21. T. Fuchs, " Noise simulation., " http://www.imp.uni-erlangen. de/forbild/deutsch/results/index.html (retrieved June 2006).