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We present a method for spatio-temporal filtration of dynamic CT data, to increase the signal-to-noise ratio (SNR) of
image data at the same time maintaining image quality, in particular spatial and temporal sharpness of the images.
Alternatively, the radiation dose applied to the patient can be reduced at the same time maintaining the noise level and
the image sharpness. In contrast to classical methods, which generally operate on the three spatial dimensions of image
data, noise statistics is improved by extending the filtration to the temporal dimension. Our approach is based on
nonlinear and anisotropic diffusion filters, which are based on a model of heat diffusion adapted to medical CT data.
Bilateral filters are a special class of diffusion filters, which do not need iteration to reach a convergence image, but
represent the fixed point of a dedicated diffusion filter.
Spatio-temporal, anisotropic bilateral filters are developed and applied to dynamic CT image data. The potential was
evaluated using data from perfusion CT and cardiac dual source CT (DSCT) data, respectively. It was shown, that in
perfusion CT, SNR can be improved by a factor of 4 at the same radiation dose. On basis of clinical data it was shown,
that alternatively the radiation dose to the patient can be reduced by a factor of at least 2. A more accurate evaluation of
the perfusion parameters blood flow, blood volume and time-to-peak is supported.
In DSCT noise statistics can be improved using more projection data than needed for image reconstruction, however, as
a consequence the temporal resolution is significantly impaired. Due to the anisotropy of the spatio-temporal bilateral
filter temporal contrast edges between adjacent time samples are preserved, at the same time substantially smoothing
image data in homogeneous regions. Also temporal contrast edges are preserved, maintaining the very high temporal
resolution of DSCT acquisitions (~ 80 ms). CT examinations of the heart require careful dose management to reduce the
radiation dose burden to the patient. The use of spatio-temporal diffusion filters allows for dose reduction at the same
noise level, at the same time preserving spatial and temporal image resolution. Our approach can be extended to any
imaging method, that is based on dynamic data, as an efficient tool for edge-preserving noise reduction.
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