• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.159-168
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• 2019

We examined the effect of Siemens ADMIRE (Advanced Modeled Iterative Reconstruction) on image quality by measuring changes in HU, noise, and SNR of background air, fat, muscle, and background signals on a chest CT scan. Experimental results show that as the ADMIRE Strength increases, the noise decreases and the signal increases, consequently the signal-to-noise ratio increases. ADMIRE can reduce noise by 28 ~ 61% compared to FBP, which is a conventional image reconstruction algorithm, and improves SNR by 16 ~ 100%.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Journal of the Korean Society of Radiology
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• v.8 no.6
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• pp.357-364
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• 2014

The filtered back projection in the image reconstruction algorithms for the clinic computed tomography system has been widely used. Noise of the reconstructed image was examined under the input noise for parallel and fan beam geometries. The reconstruction images of $512{\times}512$ size were carried out under 360 and 720 projection by the Visual C++ for parallel beam and fan beam, respectively, and those agreed with the original Shepp-Logan head phantom very much. Noise was generated because of intrinsic restriction (finite number of projections) for the image reconstruction algorithm, filtered back projection, when no input noise was applied. Because the result noise was rapidly increased under 0.5% input noise ratio, technologies for reducing noise in CT system and image processing is important.

• Journal of Radiation Protection and Research
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• v.37 no.2
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• pp.84-89
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• 2012

The purpose of this study was to compare radiation dose and image quality between low-dose (LDP) and standard-dose protocol (SDP). LDP (120 kVp, 30 mAs, 2-mm thickness) and SDP (120 kVp, 180 mAs, 1.2-mm thickness) images obtained from 61 subjects were retrospectively evaluated at level of carina bifurcation, using multi-detector CT (Brilliance 16, Philips Medical Systems). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated at ascending aorta and infraspinatus muscle, from CT number and back-ground noise. Radiation dose from two protocols measured at 5-point using acrylic-phantom, and CT number and noise measured at 4-point using water-phantom. All statistical analysis were performed using SPSS 19.0 program. LDP images showed significantly more noise and a significantly lower SNR and CNR than did SDP images at ascending aorta and infraspinatus muscle. Noise, SNR and CNR were significantly correlated with body mass index (p<0.001). Radiation dose, SNR and CNR from phantom were significant differences between two protocols. LDP showed a significant reduction of radiation dose with a significant change in SNR and CNR compared with SDP. Therefore, exposure dose on LDP in clinical applications needs resetting highly more considering image quality.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.707-712
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• 2018

The number of CT examinations is increasing, and radiation exposure is also increasing. repeated tests can affect the lens and thyroid. In hospitals, there is a tendency to lack interest in major long-term radiation exposure compared to the interest in increasing image information and image quality with head CT. In this study, we analyzed the improvement of image quality by proposed method to the noisy CT images. The proposed denoising method total variance optimization only for the impulsive noise candidate pixels. Experimental results show that edge information is well preserved and impulse noise can be effectively removed. and worked very well for the images according to tube voltage and rotation time. applied to the clinical setting, it can be used as the lowest exposure condition without worrying about the image quality and it will be helpful for the CT application.

• Journal of radiological science and technology
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• v.39 no.3
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• pp.329-336
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• 2016

The purpose of this study was to evaluate the usefulness of low-dose CT (LDCT) for emphysema compared with high-resolution CT (HRCT). Measurements of radiation dose and noise were repeated 3 times in same exposure condition which was similar with obtaining HRCT and LDCT images. We analysed reading results of 146 subjects. Six images per participants selected for emphysema grading. Emphysema was graded for all 6 zones on the left and right sides of the lungs by the consensus reading of two chest radiologists using a 4-point scale. Between the HRCT and LDCT images, diagnostic differences and agreements for emphysema were analyzed by McNemar's and unweighted kappa tests, and radiation doses and noise by a Mann-Whitney U-test, using the SPSS 19.0 program. Radiation dose from HRCT was significantly higher than that of LDCT, but the noise was significantly lower in HRCT than in LDCT. Diagnostic agreement for emphysema between HRCT and LDCT images was excellent (k-value=0.88). Emphysema grading scores were not significantly different between HRCT and LDCT images for all six lung zones. Emphysema grading scores from LDCT images were significantly correlated with increased scores on HRCT images (r=0.599, p < 0.001). Considering the tradeoff between radiation dose and image noise, LDCT could be used as the gold standard method instead of HRCT for emphysema detection and grading.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.123-129
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• 2023

The purpose of this study was to analyze differences in imaging quality and dose difference between intra-venous (IV) and intra-arterial (IA) liver dynamic computed tomography (CT). Herein, retrospective, blinded analysis was conducted to analyze signal-to-noise and contrast-to-noise ratios in cases of patients who underwent IV or IA liver dynamic CT for transarterial chemoembolization (TACE), an interventional procedure for hepatocellular carcinoma. The dose length product (DLP) value stored in Picture Archive and Communication System (PACS) was used to calculate the effective dose and thereby compare differences in the dose between the two methods. The mean liver and spleen signal to noise ratio (SNR) was greater in IV-liver dynamic CT than in IA-liver dynamic CT; however, contrast to noise ratio (CNR) was higher in IA-liver dynamic CT than in IV-liver dynamic CT. However, there were no differences in DLP and effective dose between the two methods. In conclusion, our findings showed that IA-liver dynamic CT showed a similar effective dose and superior CNR compared with IV-liver dynamic CT. Further studies must analyze 3D angiography CT of the hepatic artery to clearly distinguish the feeding artery, which is the essential step in interventional procedures for hepatocellular carcinoma.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• Journal of radiological science and technology
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• v.40 no.1
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• pp.79-85
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• 2017

The purpose of this study was to measure contrast to noise ratio (CNR) and signal to noise ratio (SNR) according to change of reconstruction from region of interest (ROI) in breast positron emission tomography-computed tomography (PET-CT), and to analyze the CNR and SNR statically. We examined images of breast PET-CT of 100 patients in a University-affiliated hospital, Seoul, Korea. Each patient's image of breast PET-CT were calculated by using ImageJ. Differences of CNR and SNR among four reconstruction algorithms were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p<0.05). We have analysis socio-demographical variables, CNR and SNR according to reconstruction images, 95% confidence according to CNR and SNR of reconstruction and difference in a mean of CNR and SNR. SNR results, with the quality of distributions in the order of PSF_TOF, Iterative and Iterative-TOF, FBP-TOF. CNR, with the quality of distributions in the order of PSF_TOF, Iterative and Iterative-TOF, FBP-TOF. CNR and SNR of PET-CT reconstruction methods of the breast would be useful to evaluate breast diseases.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.437-444
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• 2021

To evaluate the usefulness of Volume Axial Mode by comparing analyzing the exposure dose of the patients and the quality of each images from CT images obtained from high pitch mode using the local phantom or volume axial mode to determine the usefulness of he volume axial mode in diagnosing the head and cervical disease in adults. High Pitch Mode, Helical Mode, and Volume axial Mode as adult phantom were tested according to 70 kVp, 80 kVp, and 100 kVp tube voltages during an adult frontal CT scans. The equipment used was GE's Revolution (GE Healthcare, Wisconsin USA) model and iMED X-ray Phantom. The exposure dose of phantom was compared using the images obtained from each protocol, and the image quality was compared by calculating SNR and CNR by setting ROI on each image. When examined using Volume Axial Mode, the exposure dose of phantom was measured 17.12% lower than Helical Mode, 5.35% lower than High Pitch Mode, and both SNR and CNR were improved. Volume Axial Mode is a useful test that reduces investigation time without table movement using high speed rotary scanner, and in which exposure dose is reduced and image quality is improved by acquiring images in a short time of 0.28 seconds of phantom than using High Pitch Mode and Helical Mode. In addition, the fast testing time of Volume Axial Mode can be seen as the biggest advantage CT scans of emergency patients or patients with physical discomfort.