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Updated: Mar 19, 2026
Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
Published on: February 8, 2014
Low contrast detectability and spatial resolution with model-based Iterative reconstructions of MDCT images: a
Domitille Millon1, Alain Vlassenbroek2, Aline G Van Maanen3
1Department of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium. domitille.millon@uclouvain.be.
Objectives:
To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm.
Methods:
The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7 mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results.
Results:
LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses.
Conclusion:
Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent.
Key Points:
• Model- based Iterative Reconstruction improves detectability of low contrast object. • With model- based Iterative Reconstruction, spatial resolution is dose and contrast dependent. • Model-based Iterative Reconstruction algorithms enable improved IQ combined with dose-reduction possibilities. • Improvement of SR and LC detectability on the same IMR data set would reduce reconstructions.
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