• Progress in Medical Physics
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• v.28 no.1
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• pp.27-32
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• 2017

We investigated the effect of a commercial iterative reconstruction technique (iDose, Philips) on the image quality and the dose calculation for the treatment plan. Using the electron density phantom, the 3D CT images with five different protocols (50, 100, 200, 350 and 400 mAs) were obtained. Additionally, the acquired data was reconstructed using the iDose with level 5. A lung phantom was used to acquire the 4D CT with the default protocol as a reference and the low dose (one third of the default protocol) 4D CT using the iDose for the spine and lung plans. When applying the iDose at the same mAs, the mean HU value was changed up to 85 HU. Although the 1 SD was increased with reducing the CT dose, it was decreased up to 4 HU due to the use of iDose. When using the low dose 4D CT with iDose, the dose change relative to the reference was less than 0.5% for the target and OARs in the spine plan. It was also less than 1.1% in the lung plan. Therefore, our results suggests that this dose reduction technique is applicable to the 4D CT image acquisition for the radiation treatment planning.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.36-44
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• 2012

Electrical impedance tomography is a relatively new imaging modality in which the internal conductivity (or resistivity) distribution of a object is reconstructed based on the injected currents and measured voltages through the electrodes placed on the surface of the object. In this paper, it is assumed that the relationship between the resistivity distribution and the resistance of electrodes is linear. From this linear relation, the weighting matrix can be obtained and modified iterative Landweber method is applied to estimate the internal resistivity distribution. Additionally, to accelerate the convergence rate and improve the spatial resolution of the reconstructed image, optimal step lengths for the iterative Landweber method are computed from the objective function in the least-square sense. The numerical experiments have been performed to illustrate the superior reconstruction performance of the proposed scheme.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.465-472
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• 2019

To investigate the effects of iterative reconstruction algorithms on fat measurements using computed tomography (CT), we comparatively and quantitatively analyzed the ratios of visceral, subcutaneous, and visceral-subcutaneous fat areas as well as the variations of HU and noise of visceral and subcutaneous fat using ADMIRE strength and attempted to identify any difference between them. Experimental results showed that no statistically significant difference existed among the visceral, subcutaneous, and visceral-subcutaneous fat area ratios HU of visceral fat area and HU of subcutaneous fat area when applying ADMIRE as compared with existing conventional filtered back projection algorithms. However, as the ADMIRE strength increases, the noise of visceral and subcutaneous fat decreases by up to 12.1% and 19.2%, respectively. In conclusion, iterative reconstruction algorithms have no effect on the visceral, subcutaneous, and visceral-subcutaneous fat area ratios, which are indicators of fat measurement using CT.

• Progress in Medical Physics
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• v.32 no.4
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• pp.92-98
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• 2021

Purpose: This study automatically discriminates homogeneous and structure edge regions on computed tomography (CT) images, and it evaluates the noise level and edge preservation ratio (EPR) according to the different types of iterative reconstruction (IR). Methods: The dataset consisted of CT scans of 10 patients reconstructed with filtered back projection (FBP), statistical IR (iDose⁴), and iterative model-based reconstruction (IMR). Using the 10th and 85th percentiles of the structure coherence feature, homogeneous and structure edge regions were localized. The noise level was estimated using the averages of the standard deviations for five regions of interests (ROIs), and the EPR was calculated as the ratio of standard deviations between homogeneous and structural edge regions on subtraction CT between the FBP and IR. Results: The noise levels were 20.86±1.77 Hounsfield unit (HU), 13.50±1.14 HU, and 7.70±0.46 HU for FBP, iDose⁴, and IMR, respectively, which indicates that iDose⁴ and IMR could achieve noise reductions of approximately 35.17% and 62.97%, respectively. The EPR had values of 1.14±0.48 and 1.22±0.51 for iDose⁴ and IMR, respectively. Conclusions: The iDose⁴ and IMR algorithms can effectively reduce noise levels while maintaining the anatomical structure. This study suggested automated evaluation measurements of noise levels and EPRs, which are important aspects in CT image quality with patients' cases of FBP, iDose⁴, and IMR. We expect that the inclusion of other important image quality indices with a greater number of patients' cases will enable the establishment of integrated platforms for monitoring both CT image quality and radiation dose.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.240-252
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• 2023

Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.68-79
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• 2006

Electrical capacitance tomography (ECT) is a non-invasive imaging reconstruction technique that aims at visualization of cross sectional permittivity distribution of dielectric object based on the measured capacitance. There are lots of iterative image reconstruction methods to accelerate convergence rate and enhance quality of reconstructed image, Among them iterative Landweber method is one of the widely used reconstruction algorithm in En. In this paper, modified generalized Landweber method is proposed to accelerate convergence rate. In doing so, acceleration term is considered to the generalized Landweber method with shaping matrix and an optimal step length is determined analytically. Extensive computer simulations are provided to illustrate the reconstruction performance of the proposed algorithm.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.385-392
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• 2017

The purpose of this study is to investigate the image quality and exposure dose according to kVp and mAs in CT and to confirm improvement in image quality according to None IR and IR(Iterative Reconstruction) levels. Measurement results of image quality using Image J, HU(Hounsfield units) and BN(Background Noise) are decreased, while SNR(Signal to Noise Ratio) and $CTDI_{vol}$(CT dose index volume) are increased as the kVp increases and there was no change of BHU(Background Hounsfield units). BN was reduced due to increased kVp, while SNR and $CTDI_{vol}$ were increased. Also, the higher IR stage, the lower BN, SI(Signal Intensity) and HU while SNR was improved by about 10~60%. Based on this, when applying IR for clinical applications, it is necessary to finely adjust kVp and mA with a phased approach.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1025-1031
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• 2023

We aimed to evaluate the radiation dose and image quality by changing the Scout view voltage in low-dose chest CT (LDCT) and applying scan parameters such as AEC (auto exposure control) and ASIR (adaptive statistical iterative reconstruction) to find the optimal protocol. Scout view voltage was varied at 80, 100, 120, 140 kV and after measuring the dose 5 times using the existing low-dose chest CT protocol, the appropriate kV was selected for the study using the Dose report provided by the equipment. After taking a basic LDCT shot at 120 kV, 30 mAs, ASIR 50% was applied to this condition. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed by measuring Background noise (B/N). For dose comparison, CTDI_vol and DLP provided by the equipment were compared and analyzed using the formulas. The results indicated that the protocol of scout 140 + LDCT + ASIR 50 + AEC reduced radiation exposure and improved image quality compared to traditional LDCT, providing an optimal protocol. As demonstrated in the experiment, LDCT screenings for asymptomatic normal individuals are crucial, as they involve concerns over excessive radiation exposure per examination. Therefore, applying appropriate parameters is important, and it is expected to contribute positively to the public health in future LDCT based health screenings.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.578-582
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• 1994

In this paper reconstructing the internal resistivity and relative permittivity distribution is discussed. The iterative reconstruction method based on Finite Element method and Newton method were used to reconstruct both of resistivity ind permittivity distribution. The Finite Element model of impedance distribution is built in complex field of resistivity and capacitive medium. The reconstruction results based on computer simulated data and experimental data are presented.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.3
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• pp.20-25
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• 1980

A singular value decomposition (SVD) pseudo-inversion method has been applied to the image reconstruction from projections. This approach is relatively unknown and differs from conventionally used reconstructioll methods such as the Foxier convolution and iterative techniques. In this paper, two SVD pseudo-inversion methods have been discussed for the search of optimum reconstruction and restoration, one using truncated inverse filtering, the other scalar Wiener filtering. These methods partly overcome the ill-conditioned nature of restoration problems by trading off between noise and signal quality. To test the SVD pseudo-inversion method, simulations were performed from projection data obtained from a phantom using truncated inversefiltering. The results are presented together with some limitations particular to the applications of the method to the general class of 3-D image reconstruction and restoration.