The Dose Optimization and Evaluation of Image Quality in the Adult Brain Protocols of Multi-Slice Computed Tomography: A Phantom Study
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Computed tomography examinations have caused high radiation doses for patients, especially for CT scans of the brain. This study aimed to optimize the radiation dose and image quality in adult brain CT protocols. Images were acquired using a Catphan 700 phantom. Radiation doses were recorded as CTDIvol and dose length product (DLP). CT brain protocols were optimized by varying parameters such as kVp, mAs, signal-to-noise ratio (SNR) level, and Clearview iterative reconstruction (IR). The image quality was also evaluated using AutoQA Plus v.1.8.7.0 software. CT number accuracy and linearity had a robust positive correlation with the linear attenuation coefficient (µ) and showed more inaccurate CT numbers when using 80 kVp. The modulation transfer function (MTF) showed a higher value in 100 and 120 kVp protocols (p < 0.001), while high-contrast spatial resolution showed a higher value in 80 and 100 kVp protocols (p < 0.001). Low-contrast detectability and the contrast-to-noise ratio (CNR) tended to increase when using high mAs, SNR, and the Clearview IR protocol. Noise decreased when using a high radiation dose and a high percentage of Clearview IR. CTDIvol and DLP were increased with increasing kVp, mAs, and SNR levels, while the increasing percentage of Clearview did not affect the radiation dose. Optimized protocols, including radiation dose and image quality, should be evaluated to preserve diagnostic capability. The recommended parameter settings include kVp set between 100 and 120 kVp, mAs ranging from 200 to 300 mAs, SNR level within the range of 0.7–1.0, and an iterative reconstruction value of 30% Clearview to 60% or higher.Keywords:
Image noise
Optical transfer function
Contrast-to-noise ratio
A dual‐screen computed radiography (CR) technique has been developed to improve and optimize the overall image signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio (CNR). With this technique, two CR screens are exposed together and separately scanned to form a front and a back image. These two images are then superimposed to form an image of improved SNR and CNR. A mathematical model has been derived to describe the improvement and optimization of the SNR and CNR. Based on this model, the front and back images should be weighted in proportion to their SNR squared to optimize the SNR of the composite image. Imaging experiments have been conducted to verify the theoretical model under mammographic and chest imaging conditions. The results largely agree with the theoretical predictions. It has also been found that optimization of the SNR results in nearly optimal CNR and vice versa. For mammographic imaging, a 14%–22% improvement in the SNR and a 13%–19% improvement in the CNR have been demonstrated. For chest imaging, a 31%–36% improvement in the SNR and a 28%–30% improvement in the CNR has been demonstrated.
Contrast-to-noise ratio
Computed radiography
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The purpose of this study was to assess the impact of a noise reduction technique on image quality, radiation dose, and low-contrast detectability in abdominal CT for obese patients.A liver phantom with 12 different tumors was designed, and fat rings were added to mimic intermediately sized and large patients. The intermediate and large phantoms were scanned with our standard abdominal CT protocol (image noise level of 15 HU and filtered back projection [FBP]). The large phantom was scanned with five different noise levels (10, 12.5, 15, 17.5, and 20 HU). All datasets for the large phantom were reconstructed with FBP and the noise reduction technique. The image noise and the contrast-to-noise ratio (CNR) were assessed. Tumor detection was independently performed by three radiologists in a blinded fashion.The application of the noise reduction method to the large phantom decreased the measured image noise (range, -14.5% to -37.0%) and increased the CNR (range, 26.7-70.6%) compared with FBP at the same noise level (p < 0.001). However, noise reduction was unable to improve the sensitivity for tumor detection in the large phantom compared with FBP at the same noise level (p > 0.05). Applying a noise level of 15 HU, the overall sensitivity for tumor detection in the intermediate and large phantoms with FBP measured 75.5% and 87.7% and the radiation doses measured 42.0 and 23.7 mGy, respectively.Although noise reduction significantly improved the quantitative image quality in simulated large patients undergoing abdominal CT compared with FBP, no improvement was observed for low-contrast detectability.
Image noise
Contrast-to-noise ratio
Abdominal computed tomography
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Image noise
Contrast-to-noise ratio
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The contrast-to-noise ratio (CNR) is presented and characterized as a tool for quantitative noise measurement of scanning electron microscope (SEM) images. Analogies as well as differences between the CNR and the widely used signal-to-noise ratio (SNR) are analytically and experimentally investigated. With respect to practical SEM image evaluation using the contrast-to-noise ratio, a standard specimen and an evaluation program are presented.
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Image noise
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Objectives To evaluate the application of iterative reconstruction(iDose4) for reducing radiation dose and controlling image quality in prospective electrocardiogram(ECG)-gated computed tomography(CT) combined with weight adjusting tube voltage and current. Methods Ten pigs were included. All the pigs were scanned on a 256-slice prospective ECG-gated multilayer spiral CT system utilizing routine dose(group A) based on weight adjusting tube voltage and current and tube current reduced by 30%(group B), 50%(group C) and 70%(group D) respectively.Filtered back-projection(FBP) and iDose4were used for reconstruction respectively for all data. Radiation dose were calculated and noise, signal-to-noise ratio(SNR), contrast-to-noise rate(CNR) of ascending aortic root and left ventricle were measured, while general image quality and coronary artery image quality were graded(scale:1-5). All results reconstructed by FBP and iDose4were compared. Results The effective radiation doses for group A,B,C,D were(3.13 ±0.63) mSv,(2.26 ±0.51) mSv,(1.61 ±0.36) mSv,(1.01 ±0.23) mSv. The image noise increased as well as SNR, CNR and image quality decreased with the X-ray dose decreased. Image noise significantly decreased, while SNR and CNR obviously increased with iDose4reconstruction in each group(all P=0.000). For FBP / iDose4reconstruction,there were evident differences of image quality in group A(3.80±0.42 vs. 4.60±0.52, P0.05), group B(3.60±0.52vs. 4.40±0.52, P0.05), group C(3.00±0.67 vs. 3.80±0.42, P0.05) and group D(2.00±0.67 vs. 3.40±0.52, P 0.05). The diagnosed rates of proximal, distal coronary artery in group A, B, C, D with FBP reconstruction were100%, 95%, 70%, 20% and 92%, 72%, 36%, 0 respectively, while the diagnosed rates of proximal, distal coronary artery in group A, B, C with iDose4were not lower than those in group A with FBP(P0.05), whereas the diagnosed rates in group D with iDose4were significantly lower than those in group A with FBP(P0.05). Conclusions IDose4can sharply reduce image noise, improve SNR,CNR and image quality compared with FBP in prospective ECG-gated coronary CT combined with weight adjusting tube voltage and current. It's workable with a 50% reduction in radiation dose, while the image quality remains the same.
Image noise
Contrast-to-noise ratio
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Contrast-to-noise ratio
Digital Mammography
Carrier-to-noise ratio
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Objective To assess the impact of different exposure tube voltage and mAs on pixel mean value,noise and contrast to noise ratio(CNR) of image in regions of interest,in order to recommend the best exposure parameters to reduce radiation dose on the condition of good image quality.Methods One group kept the mAs constantly(the mAs was used in conventional bedside X-ray photography) and raised the tube voltage from 55 kVp to 120 kVp by step of 5 kVp.Four suitable kVp values were selected out from first experiment and the mAs was raised from 1.00 to 5 by 7.00 steps as the second experiment.The pixel mean value and noise of the image in region of interest were measured and recorded in 2 density areas,and the CNR was calculated.Results The pixel mean value of the image in region of interest was not influenced by the exposure tube voltage or mAs.The exposure condition affected the noise and CNR: When tube voltage was 80 kVp,the noise decreased and CNR remarkably as tube voltage raised.When tube voltage was ≥80 kVp,increase of tube voltage affected the noise and CNR indistinctly.Keeping the tube valtage in 4 different values,the mAs influenced the noise and CNR: When mAs was 2.00,the noise decreased remarkably as the mAs raised.When mAs was ≥2.00,raising mAs affected less and less on the noise and CNR.Conclusion The suggested tube voltage of the chest radiography by DR is from 75 kVp to 85 kVp,depending on patients' form,and the suggested mAs is from 2.00 to 3.0 0 for obtaining better image quality and less patients' X-ray dose.
Image noise
Contrast-to-noise ratio
Digital radiography
Computed radiography
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Purpose: To compare image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of different cardiac MRI sequences for tissue characterization and functional analysis at 1.5 T and 3.0 T in volunteers.
Contrast-to-noise ratio
SIGNAL (programming language)
Image contrast
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Objective To assess the effect of field strength on magnetic resonance imaging of knee.Methods 16 healthy volunteers were imaged at two similarly equipped MR imagers of the same generation and from the same manufacturer.The same imaging sequences were used with identical parameters and without repetition time correction for field strength.Imaging was performed in the same anatomic locations: the knee.Quantitative image analysis involved calculation of signal-to-noise ratio,contrast-to-noise ratio and relative contrast.Results SNR(signal-to-noise ratio) and CNR(contrast-to-noise ratio) increased nonlinearly with field strength,3.0T was judged superior to 1.5T images(P0.05),relative contrast was not as dependent on field strength.Image quality was judged to be equivalent at 1.5T and 3.0 T.Conclusion Excellent image quality was obtained with two kinds of field strengths.Compared to 1.5T,SNR and CNR were promoted at 3.0T.However,relative contrast had no significant differences.
Field strength
Contrast-to-noise ratio
Signal strength
Image contrast
Echo time
Contrast ratio
SIGNAL (programming language)
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