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Experimental investigation of angular stackgram filtering for noise reduction of SPECT projection data: study with linear and nonlinear filters.

Happonen AP, Koskinen MO - Int J Biomed Imaging (2007)

Bottom Line: We discuss data filtering prior to image reconstruction.Our study is carried out by employing simple linear and nonlinear filters with ten different Gaussian kernels, in order to provide a comparable investigation.According to our results, angular stackgram filtering with the nonlinear filters provides the best resolution-noise tradeoff of the compared methods.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Physiology, Medical Imaging Center, Tampere University Hospital, P.O. Box 2000, 33521 Tampere, Finland.

ABSTRACT
We discuss data filtering prior to image reconstruction. For this kind of filtering, the radial direction of the sinogram is routinely employed. Recently, we have introduced an alternative approach to sinogram data processing, exploiting the angular information in a novel way. This new stackgram representation can be regarded as an intermediate form of the sinogram and image domains. In this experimental study, we compare the radial sinogram and angular stackgram filtering methods using physical SPECT phantoms. Our study is carried out by employing simple linear and nonlinear filters with ten different Gaussian kernels, in order to provide a comparable investigation. According to our results, angular stackgram filtering with the nonlinear filters provides the best resolution-noise tradeoff of the compared methods. Besides, stackgram filtering with these filters seems to preserve the resolution in an exceptional way. Visually, noise in the reconstructed images after stackgram filtering appears more "powdery" in comparison with radial sinogram filtering.

No MeSH data available.


Related in: MedlinePlus

In (a), the sinogram is composed of sinusoidalsignals. In SPECT, the sinusoids complete one cycle, that is, a full 360-degreeview with different amplitudes and phases (the shown view corresponds to 180∘). The signalsalong the sinusoids contribute to the points or pixels in the reconstructedimage, as shown in (b). The amplitude and phase of the sinusoidal signals (a)vary depending on the distance and spatial location of the points in the image(b).
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fig1: In (a), the sinogram is composed of sinusoidalsignals. In SPECT, the sinusoids complete one cycle, that is, a full 360-degreeview with different amplitudes and phases (the shown view corresponds to 180∘). The signalsalong the sinusoids contribute to the points or pixels in the reconstructedimage, as shown in (b). The amplitude and phase of the sinusoidal signals (a)vary depending on the distance and spatial location of the points in the image(b).

Mentions: A different approach to the quantum noise reduction issmoothing or filtering of the raw projection or sinogram data before imagereconstruction. Then, in principle, simple and linear filtered back-projection(FBP) reconstruction can result in sufficient images, in terms of uniformresolution and contrast. Traditionally, the sinogram (see Figure 1) data arefiltered only in the radial direction (i.e., along the projections). Well-knownexamples of radial data filtering are, for example, the Hanning and Butterworthlowpass filters [4],which are routinely employed in FBP reconstruction. In contrast, filteringalong the angular direction of the data(i.e., across the projections ofdifferent angular views) is usually avoided since it introduces tangentiallyvarying blurring into the reconstructed image [5].


Experimental investigation of angular stackgram filtering for noise reduction of SPECT projection data: study with linear and nonlinear filters.

Happonen AP, Koskinen MO - Int J Biomed Imaging (2007)

In (a), the sinogram is composed of sinusoidalsignals. In SPECT, the sinusoids complete one cycle, that is, a full 360-degreeview with different amplitudes and phases (the shown view corresponds to 180∘). The signalsalong the sinusoids contribute to the points or pixels in the reconstructedimage, as shown in (b). The amplitude and phase of the sinusoidal signals (a)vary depending on the distance and spatial location of the points in the image(b).
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2266980&req=5

fig1: In (a), the sinogram is composed of sinusoidalsignals. In SPECT, the sinusoids complete one cycle, that is, a full 360-degreeview with different amplitudes and phases (the shown view corresponds to 180∘). The signalsalong the sinusoids contribute to the points or pixels in the reconstructedimage, as shown in (b). The amplitude and phase of the sinusoidal signals (a)vary depending on the distance and spatial location of the points in the image(b).
Mentions: A different approach to the quantum noise reduction issmoothing or filtering of the raw projection or sinogram data before imagereconstruction. Then, in principle, simple and linear filtered back-projection(FBP) reconstruction can result in sufficient images, in terms of uniformresolution and contrast. Traditionally, the sinogram (see Figure 1) data arefiltered only in the radial direction (i.e., along the projections). Well-knownexamples of radial data filtering are, for example, the Hanning and Butterworthlowpass filters [4],which are routinely employed in FBP reconstruction. In contrast, filteringalong the angular direction of the data(i.e., across the projections ofdifferent angular views) is usually avoided since it introduces tangentiallyvarying blurring into the reconstructed image [5].

Bottom Line: We discuss data filtering prior to image reconstruction.Our study is carried out by employing simple linear and nonlinear filters with ten different Gaussian kernels, in order to provide a comparable investigation.According to our results, angular stackgram filtering with the nonlinear filters provides the best resolution-noise tradeoff of the compared methods.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Physiology, Medical Imaging Center, Tampere University Hospital, P.O. Box 2000, 33521 Tampere, Finland.

ABSTRACT
We discuss data filtering prior to image reconstruction. For this kind of filtering, the radial direction of the sinogram is routinely employed. Recently, we have introduced an alternative approach to sinogram data processing, exploiting the angular information in a novel way. This new stackgram representation can be regarded as an intermediate form of the sinogram and image domains. In this experimental study, we compare the radial sinogram and angular stackgram filtering methods using physical SPECT phantoms. Our study is carried out by employing simple linear and nonlinear filters with ten different Gaussian kernels, in order to provide a comparable investigation. According to our results, angular stackgram filtering with the nonlinear filters provides the best resolution-noise tradeoff of the compared methods. Besides, stackgram filtering with these filters seems to preserve the resolution in an exceptional way. Visually, noise in the reconstructed images after stackgram filtering appears more "powdery" in comparison with radial sinogram filtering.

No MeSH data available.


Related in: MedlinePlus