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Proceedings Paper

Model based iterative reconstruction IMR gives possibility to evaluate thinner slice thicknesses than conventional iterative reconstruction iDose4: a phantom study
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Paper Abstract

Computed tomography (CT) is one of the most important modalities in a radiological department, which produces images with high diagnostic confidence, but in some cases contributes to a high radiation dose to the patient. The radiation dose can be reduced by the use of advanced image reconstruction algorithms. This study was done on a Philips Brilliance iCT with iterative reconstruction iDose4 and model-based iterative reconstruction IMR. The purpose was to investigate the effect on the image quality with thin slice images reconstructed with IMR, compared to standard slice thickness reconstructed with iDose4. Objective measurements of noise and contrast-to-noise ratio were performed using an image quality phantom, an anthropomorphic phantom and clinical cases. Subjective evaluations of low-contrast resolution were performed by observers using an image quality phantom. IMR gives strong noise reduction and enhanced low-contrast and thereby enable selection of thinner slice thickness. Objective evaluation of image noise shows that thin slices reconstructed with IMR provides lower noise than thicker slice images reconstructed with iDose4. With IMR the slice thickness is of less importance for the noise. With thinner slices the partial volume artefacts becomes less pronounced. In conclusion, we have shown that IMR enables reduction of the slice thickness and at the same time maintain or even reduce the noise level compared to iDose4 reconstruction with standard slice thickness. This will subsequently result in an improvement of image quality for images reconstructed with IMR.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94124I (18 March 2015); doi: 10.1117/12.2081824
Show Author Affiliations
Marie-Louise Aurumskjöld, Lund Univ. (Sweden)
Skåne Univ. Hospital (Sweden)
Kristina Ydström, Philips Healthcare (Sweden)
Anders Tingberg, Lund Univ. (Sweden)
Skåne Univ. Hospital (Sweden)
Marcus Söderberg, Lund Univ. (Sweden)
Skåne Univ. Hospital (Sweden)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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