• Journal of radiological science and technology
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• v.45 no.1
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• pp.11-17
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• 2022

This study was purpose to quantitative assessment of the resolution characteristics by using American college of radiology(ACR) phantom for magnetic resonance imaging (MRI). The MRI equipment was used (Achiva 3.0T MRI, Philips system, Netherlands) and the head/neck matrix shim SENSE head coil were 32 channels(elements) receive MR coil. And the MRI equipment was used (Discovery MR 750, 3.0T MRI, GE medical system, America) and the head/neck matrix shim MC 3003G-32R 32-CH head coil were receive MR coil. As for the modulation transfer function(MTF) comparison result by using ACR magnetic resonance imaging phantom, the MTF value of the ACR standard T2 image in GE equipment is 0.199 when the frequency is 1.0 mm^-1 and the MTF value of the hospital T2 image in Philips equipment is 0.528. It was used efficiently by using a general sequence more than the standard sequence method using the ACR phantom. In addition it is significant that the quantitative quality assurance evaluation method for resolution characteristics was applied mutatis mutandis, and the result values of the physical image characteristics of the 3.0T MRI device were presented.

• Journal of Radiation Protection and Research
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• v.37 no.1
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• pp.41-49
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• 2012

The objective of this study is for development of the reference Korean female phantom, HDRK-Woman. The phantom was constructed by adjusting a Korean woman voxel phantom to the Reference Korean data. The Korean woman phantom had been developed based on the high-resolution color slice images obtained from an adult Korean female cadaver. There were a total of 39 organs including the 27 organs specified in ICRP 103 for effective dose calculation. The voxel resolution of the phantom was $1.976{\times}1.976{\times}2.0619\;mm^3$ and the voxel array size is $261{\times}109{\times}825$ in the x, y and z directions. Then, the voxel resolution was changed to $2.0351{\times}2.0351{\times}2.0747\;mm^3$ for adjustment of the height and total bone mass of the phantom to the Reference Korean data. Finally, the internal organs and tissue were adjusted using in-house software program developed for 3D volume adjustment of the organs and tissue. The effective dose values of HDRK phantoms were calculated for broad parallel photon beams using MCNPX Monte Carlo code and compared with those of ICRP phantoms.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.87-92
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• 2015

Purpose When the patients takes myocardial perfusion SPECT using $^{201}Tl$, the operator gives the patients an injection of $^{201}Tl$. But the uniformity correction map in SPECT uses $^{99m}Tc$ uniformity correction map. Thus, we want to compare the image quality when it uses $^{99m}Tc$ uniformity correction map and when it uses $^{201}Tl$ uniformity correction map. Materials and Methods Phantom study is performed. We take the data by Asan medical center daily QC condition with flood phantom including $^{201}Tl$ 21.3 kBq/mL. After postprocessing with this data, we analyze CFOV integral uniformity(I.U) and differential uniformity(D.U). And we take the data with Jaszczak ECT Phantom by American college of radiology accreditation program instruction including $^{201}Tl$ 33.4 kBq/mL. After post processing with this data, we analyze spatial Resolution, Integral Uniformity(I.U), coefficient of variation(C.V) and Contrast with Interactive data language program. Results In the flood phantom test, when it uses $^{99m}Tc$ uniformity correction map, Flood I.U is 3.6% and D.U is 3.0%. When it uses $^{201}Tl$ uniformity correction map, Flood I.U is 3.8% and D.U is 2.1%. The flood I.U is worsen about 5%, but the D.U is improved about 30% inversely. In the Jaszczak ECT phantom test, when it uses $^{99m}Tc$ uniformity correction map, SPECT I.U, C.V and contrast is 13.99%, 4.89% and 0.69. When it uses $^{201}Tl$ uniformity correction map, SPECT I.U, C.V and contrast is 11.37%, 4.79% and 0.78. All of data are improved about 18%, 2%, 13% The spatial resolution was no significant changes. Conclusion In the flood phantom test, Flood I.U is worsen but Flood D.U is improved. Therefore, it's uncertain that an image quality is improved with flood phantom test. On the other hand, SPECT I.U, C.V, Contrast are improved about 18%, 2%, 13% in the Jaszczak ECT phantom test. This study has limitations that we can't take all variables into account and study with two phantoms. We need think about things that it has a good effect when doctors decipher the nuclear medicine image and it's possible to improve the image quality using the uniformity correction map of other radionuclides other than $^{99m}Tc$, $^{201}Tl$ when we make other nuclear medicine examinations.

• Journal of Biomedical Engineering Research
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• v.11 no.1
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• pp.113-120
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• 1990

In this paper, the deconvolution method utilizing a modified Wiener filter is applied for the enhancement of lateral resolution of ultrasonic B-scan Images. For this purpose, a phantom composed of wires which are 0.6mm of diameter and apart in the range between 3 to 9mm is constructed. The modified Wiener filter with optimal parameter is applied to the phantom for the analysis of ultrasonic image. The results obtained are as follows'When all parameters of the modified Wiener filter are optimal, the resolution of B-scan images is enhanced by 50 percent : Othenrise, the images are blurred, spilt at peak points, or noises are strengthened severely. When the point-spread function representing the characteristic function of the system is determined, the selection ranges of op- timum parameters may be narrowed. It is expected that the proposed method may be able to apply to clinic situations for more accurate image analysis by means of reducing the loss of important information.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.814-821
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• 2011

The purpose of this study was to evaluate of resolution parameter and reconstitution filter in the 256 multi detector computed tomography(MDCT) by using the head phantom. We used 256 MDCT, and head phantom of philips system. We evaluated to image quality by using Extended Brilliance Workspace. The protocol were axial scan method with 120 kVp, 0.5 sec of rotation time, 5 mm of slice thickness and increment, 250 mm of field of view(FOV), $512{\times}512$ of matrix size, 1.0 of pitch, $128{\times}0.625$ mm of collimations. The resolution parameter was applied for 'Standard', 'High' and 'Ultrahigh'. The reconstitution filters were changed to seven type of 'A', 'B', 'C', 'D', 'UA', 'UB', 'UC'. The assesment factors of image quality were the uniformity, the noise, the linearity and 50% and 10% of the modulation transfer function(MTF). Finally The good image quality in 'High' resolution parameter showed at the uniformity, the linearity and 50% and 10% of MTF. The 'UA', 'UB' reconstitution filter showed at the good image quality of the uniformity and the noise and 'C' reconstitution filter showed at the same result of the linearity and 50% and 10% of MTF.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.

• Journal of the Korean Society of Radiology
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• v.6 no.3
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• pp.217-226
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• 2012

This study examines image quality of medical image after compression using JPEG2000 for AAPM CT Performance Phantom in PACS. The compressed images of 15:1 showed change of 1.93% and 0.81% in the CT number of water and the slice thickness, respectively, compared to the original images. The variation of the uniformity did not give a correlation for each measured area. In noise measurements at compressions of 10:1 and 15:1, changes of 1.47% to 10.99% were observed, respectively. The noise showed incremation tendency as increasing over the compression ratio 15:1, and the noise of 81.68% was measured at a compression of 40:1. CT number, uniformity, slice thickness, spatial resolution and contrast resolution for the compressed images were slightly changed by increasing the compression ratio. However, the noise was seriously changed relatively at the compressed images. Thus the noise was a important factor to determine the compression ration. A compression ratio of 10:1 for the AAPM CT Performance Phantom image was appropriate and could be applied to diagnostic images.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.114-123
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• 2007

The increasing use of computed tomography (CT) as a diagnostic tool creates the need from and efficient means of evaluating the performance of the CT scanner now in use. Accordingly, acceptance testing and quality assurance of CT is of great importance. The aim of this study is to analyze of AAPM CT performance phantom in the CT accreditation program. The modular phantom offers the CT system with which to measure eight performance parameters. The parameters are listed of CT attenuation coefficient of water, noise, uniformity, spatial resolution, contrast resolution, slice thickness (5 and 10 mm), artifacts and alignment. The phantom evaluation was done by two radiologists. The acceptance testing protocol described here in demonstrates the successful of the guidelines for the quality assurance using AAPM CT performance phantom. We need to be upgraded for the CT image quality and make the standard reference of the quality assurance in the CT.

• Progress in Medical Physics
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• v.19 no.2
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• pp.120-124
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• 2008

In this study, we developed the protopype of QA phantom for image QA including an additional component for image based radiation treatment system. The new phantom considered two main parts: Image quality and fusion accuracy. Image quality part included for daily CT number linearity and spatial resolution, and fusion accuracy part designed to simulate a simple translation-rotation setting. The CT scans of the phantom obtained from conventional CT, MVCT of Tomotherapy unit, and both image sets were satisfied the recommendation of spatial resolution. This phantom was simple and efficient for daily imaging QA, and it is important to provide a new concept of verification of image registration.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.67-71
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• 2013

Purpose: The Change of CT exposure condition have a effect on image quality and patient exposure dose. In this study, we evaluated effect CT image quality and SUV when CT parameters (Pitch, Rotation time) were changed. Materials and Methods: Discovery Ste (GE, USA) was used as a PET/CT scanner. Using GE QA Phantom and AAPM CT Performance Phantom for evaluate Noise of CT image. Images are acquired by using 24 combinations that four stages pitch (0.562, 0.938, 1.375, 1.75:1) and six stages X-ray tube rotation time (0.5s-1.0s). PET images are acquired using 1994 NEMA PET Phantom ($^{18}F-FDG$ 5.3 kBq/mL, 2.5 min/frame). For noise test, noise are evaluated by standard deviation of each image's CT numbers. And then we used expectation noise according to change of DLP (Dose Length Product) to experimental noise ratio for index of effectiveness. For spatial resolution test, we confirmed that it is possible to identify to 1.0 mm size of the holes at the AAPM CT Performance Phantom. Finally we evaluated each 24 image's SUV. Results: Noise efficiency were 1.00, 1.03, 1.01, 0.96 and 1.00, 1.04, 1.02, 0.97 when pitch changes at the QA Phantom and AAPM Phantom. In case of X-ray tube rotation time changes, 0.99, 1.02, 1.00, 1.00, 0.99, 0.99 and 1.01, 1.01, 0.99, 1.01, 1.01, 1.01 at the QA Phantom and AAPM Phantom. We could identify 1.0 mm size of the holes all 24 images. Also, there were no significant change of SUV and all image's average SUV were 1.1. Conclusion: 1.75:1 pitch is the most effective value at the CT image evaluation according to pitch change and It doesn't affect to the spatial resolution and SUV. However, the change of rotation time doesn't affect anything. So, we recommend to use the effective pitch like 1.75:1 and adequate X-ray tube rotation time according to patient size.