Abstract
Purpose
To compare the noise and accuracy on images of the whole porcine liver acquired with
iterative reconstruction (IMR, Philips Healthcare, Cleveland, OH, USA) and filtered
back projection (FBP) methods.
Materials and methods
We used non-enhanced porcine liver to simulate the human liver and acquired it 100
times to obtain the average FBP value as the ground-truth. The mean and the standard
deviation (“inter-scan SD”) of the pixel values on the 100 image acquisitions were
calculated for FBP and for three levels of IMR (L1, L2, and L3). We also calculated
the noise power spectrum (NPS) and the normalized NPS for the 100 image acquisitions.
Results
The spatial SD for the porcine liver parenchyma on these slices was 9.92, 4.37, 3.63,
and 2.30 Hounsfield units with FBP, IMR-L1, IMR-L2, and IMR-L3, respectively. The
detectability of small faint features was better on single IMR than single FBP images.
The inter-scan SD value for IMR-L3 images was 53% larger at the liver edges than at
the liver parenchyma; it was only 10% larger on FBP images. Assessment of the normalized
NPS showed that the noise on IMR images was comprised primarily of low-frequency components.
Conclusion
IMR images yield the same structure informations as FBP images and image accuracy
is maintained. On level 3 IMR images the image noise is more strongly suppressed than
on IMR images of the other levels and on FBP images.
Keywords
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References
- Iterative reconstruction methods in X-ray CT.Phys Med. 2012; 28: 94-108
- CT iterative reconstruction in image space: a phantom study.Phys Med. 2012; 28: 161-165
- Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments – a phantom approach.Phys Med. 2013; 29: 99-110
- Optimisation of an MDCT abdominal protocol: image quality assessment of standard vs. iterative reconstructions.Phys Med. 2014; 30: 271-279
- Detection of myocardial perfusion abnormalities using ultra-low radiation dose regadenoson stress multidetector computed tomography.J Cardiovasc Comput Tomogr. 2011; 5: 247-254
- Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary CT angiography.AJR Am J Roentgenol. 2010; 195: 649-654
- A clinical comparison study of a novel statistical iterative and filtered backprojection reconstruction.Proc SPIE. 2011; 7961
- Combination of a low-tube-voltage technique with hybrid iterative reconstruction (iDose) algorithm at coronary computed tomographic angiography.J Comput Assist Tomogr. 2011; 35: 480-485
- Radiation dose reduction with hybrid iterative reconstruction for pediatric CT.Radiology. 2012; 263: 537-546
- Low contrast agent and radiation dose protocol for hepatic dynamic CT of thin adults at 256-detector row CT: effect of low tube voltage and hybrid iterative reconstruction algorithm on image quality.Radiology. 2012; 264: 445-454
- Radiation dose reduction in abdominal computed tomography during the late hepatic arterial phase using a model-based iterative reconstruction algorithm: how low can we go?.Invest Radiol. 2012; 47: 468-474
- Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique.Eur Radiol. 2012; 22: 1613-1623
- Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique.Eur J Radiol. 2012; 81: e363-e369
- Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms.Med Phys. 2012; 39: 4115-4122
- Achieving routine submillisievert CT scanning: report from the summit on management of radiation dose in CT.Radiology. 2012; 264: 567-580
- Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta.Phys Med Biol. 2007; 52: 4027-4046
- Application of the noise power spectrum in modern diagnostic MDCT: part II. Noise power spectra and signal to noise.Phys Med Biol. 2007; 52: 4047-4061
- Noise properties of maximum likelihood reconstruction with edge-preserving regularization in transmission tomography.Fully 3D. 2009; : 263-266
Article info
Publication history
Published online: March 24, 2014
Accepted:
February 27,
2014
Received in revised form:
February 19,
2014
Received:
September 11,
2013
Identification
Copyright
© 2014 Published by Elsevier Inc.
