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Proceedings Paper

Novel iterative reconstruction method for optimal dose usage in redundant CT - acquisitions
Author(s): H. Bruder; R. Raupach; T. Allmendinger; S. Kappler; J. Sunnegardh; K. Stierstorfer; T. Flohr
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Paper Abstract

In CT imaging, a variety of applications exist where reconstructions are SNR and/or resolution limited. However, if the measured data provide redundant information, composite image data with high SNR can be computed. Generally, these composite image volumes will compromise spectral information and/or spatial resolution and/or temporal resolution. This brings us to the idea of transferring the high SNR of the composite image data to low SNR (but high resolution) ‘source’ image data. It was shown that the SNR of CT image data can be improved using iterative reconstruction [1] .We present a novel iterative reconstruction method enabling optimal dose usage of redundant CT measurements of the same body region. The generalized update equation is formulated in image space without further referring to raw data after initial reconstruction of source and composite image data. The update equation consists of a linear combination of the previous update, a correction term constrained by the source data, and a regularization prior initialized by the composite data. The efficiency of the method is demonstrated for different applications: (i) Spectral imaging: we have analysed material decomposition data from dual energy data of our photon counting prototype scanner: the material images can be significantly improved transferring the good noise statistics of the 20 keV threshold image data to each of the material images. (ii) Multi-phase liver imaging: Reconstructions of multi-phase liver data can be optimized by utilizing the noise statistics of combined data from all measured phases (iii) Helical reconstruction with optimized temporal resolution: splitting up reconstruction of redundant helical acquisition data into a short scan reconstruction with Tam window optimizes the temporal resolution The reconstruction of full helical data is then used to optimize the SNR. (iv) Cardiac imaging: the optimal phase image (‘best phase’) can be improved by transferring all applied over radiation into that image. In all these cases, we show that - at constant patient dose - SNR can efficiently be transferred from the composite data to the source data while maintaining spatial, temporal and contrast resolution properties of the source data.

Paper Details

Date Published: 19 March 2014
PDF: 10 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90330P (19 March 2014); doi: 10.1117/12.2042985
Show Author Affiliations
H. Bruder, Siemens HealthCare (Germany)
R. Raupach, Siemens HealthCare (Germany)
T. Allmendinger, Siemens HealthCare (Germany)
S. Kappler, Siemens HealthCare (Germany)
J. Sunnegardh, Siemens HealthCare (Germany)
K. Stierstorfer, Siemens HealthCare (Germany)
T. Flohr, Siemens HealthCare (Germany)


Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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