• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.7-15
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• 2003

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.211-220
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• 2020

High-quality computed tomography (CT) images enable precise lesion detection and accurate diagnosis. A lot of studies have been performed to improve CT image quality while reducing radiation dose. Recently, deep learning-based techniques for improving CT image quality have been developed and show superior performance compared to conventional techniques. In this study, a super-resolution convolutional neural network (SRCNN) model was used to improve the spatial resolution of CT images, and image quality according to the hyperparameters, which determine the performance of the SRCNN model, was evaluated in order to verify the effect of hyperparameters on the SRCNN model. Profile, structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and full-width at half-maximum (FWHM) were measured to evaluate the performance of the SRCNN model. The results showed that the performance of the SRCNN model was improved with an increase of the numbers of epochs and training sets, and the learning rate needed to be optimized for obtaining acceptable image quality. Therefore, the SRCNN model with optimal hyperparameters is able to improve CT image quality.

• Journal of the Korean Society of Radiology
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• v.83 no.1
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• pp.54-69
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• 2022

Early detection of potential asymptomatic coronary artery disease is very important, as patients with sudden cardiac death often do not show symptoms such as chest pain or motor dyspnea. Coronary CT angiography (CCTA) has long been unjustified as a screening tool for asymptomatic patients because of the risks posed by radiation exposure. However, there are still various opinions regarding the usefulness of CCTA for screening for coronary artery disease (CAD) in asymptomatic healthy individuals or patients. This review investigated the usefulness of coronary artery calcium score and CCTA as screening tests for CAD in asymptomatic healthy individuals or patients through various literature reviews. With the development of CT technology, recent studies have been conducted in asymptomatic CAD patients with a reduced radiation dose of less than 1 mSv. A total of 2.6% of asymptomatic subjects on CCTA found significant CAD over 70%, and it was concluded that screening CCTA for CAD showed prognostic power in predicting the future occurrence of CAD in asymptomatic people. However, after the completion of the current NIH SCOT-HEART 2 study, it may be possible to determine whether CCTA is appropriate as a screening tool for CAD in asymptomatic healthy individuals.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.143-147
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• 2016

Recently, digital tomosynthesis system (DTS) has been developed to reduce overlap using conventional X-ray and to overcome high patient dose problem using computed tomography (CT). The purpose of this study was to develop image reconstruction algorithm and to evaluate image characteristics and dose with chest digital tomosynthesis (CDT) system. Image reconstruction was used for filtered back-projection (FBP) methods and system geometry was constructed ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, and ${\pm}30^{\circ}$ angular range for acquiring phantom images. Image characteristics carried out root mean square error (RMSE) and signal difference-to-noise ratio (SDNR), and dose is evaluated effective dose with ${\pm}20^{\circ}$ angular range. According to the results, the phantom image with slice thickness filter has superb RMSE and SDNR, and effective dose was 0.166 mSv. In conclusion, we demonstrated usefulness of developed CDT image reconstruction algorithm and we constructed CDT basic output data with measuring effective dose.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.543-547
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• 2016

Acute stroke is a one of common disease that require fast diagnosis and treatment to save patients life. however, the acute stroke may cause lifelong disability due to brain damage with no prompt surgical procedure. In order to diagnose the Stroke, brain perfusion CT examination and possible rapid implementation of 3D angiography has been widely used. However, a low-dose technique should be applied for the examination since a lot of radiation exposure to the patient may cause secondary damage for the patients. Therefore, the degradation of the measured CT images may interferes with a clinical check in that blood vessel shapes on the CT image are significantly affected by gaussian noise. In this study, we employed the spatio-temporal technique to analyze dynamic (brain perfusion) CT data to improve an image quality for successful clinical diagnosis. As a results, proposed technique could remove gaussian noise successfully, demonstrated a possibility of new image segmentation technique for CT angiography. Qualitative evaluation was conducted by skilled radiological technologists, indicated significant quality improvement of dynamic CT images. the proposed technique will be useful tools as a clinical application for brain perfusion CT examination.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.17-18
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• 2024

악성 흉수의 진단은 세포학적 검사로 암세포를 확인하는 것이 필수적이며 진단율은 50~80%로 나타난다. 양성자 단층 촬영은 비침습적으로 암 병기를 평가하는 유용한 방법이다. 하지만 암이 아닌 다른 원인으로 인한 포도당 대사로 인하여 양전자 단층 촬영만으로 악성 흉수를 진단하는 데 어려움이 있다. 악성 흉수 자동 진단 모델은 암세포를 진단하는데 있어서 보조적인 역할이 가능하다. 이에 따라 본 연구는 컨볼루션 신경망 기반의 딥러닝 모델을 개발하여 악성 흉수 진단 성능을 확인하고 진단의 보조적 목적으로써 딥러닝의 사용 가능성을 확인하고자 하였다. 결과적으로 모델 전반적으로 accuracy 0.7~0.86의 높은 성능을 보였다. 본 연구의 결과를 통해 실제 의료 환경에서 악성 흉수를 진단하는데 딥러닝 모델이 보조적인 역할을 할 수 있을 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.11-16
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• 2005

Recently, there are a lot of endeavor to implement a fuzzy theory to artificial neural network. Goh proposed the fuzzy single layer perceptron algorithm and advanced fuzzy perceptron based on the generalized delta rule to solve the XOR Problem and the classical Problem. However, it causes an increased amount of computation and some difficulties in application of the complicated image recognition. In this paper, we propose an enhanced fuzzy single layer Perceptron using the dynamic adjustment of threshold. This method is applied to the XOR problem, which used as the benchmark in the field of pattern recognition. The method is also applied to the recognition of digital image for image application. In a result of experiment, it does not always guarantee the convergence. However, the network show improved the learning time and has the high convergence rate.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.241-246
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• 2017

The existing fractal compression method is effective in generating an artificial shape by approximating its partial regions to a domain block by re-dividing the whole image into a domain region and dividing it into several domain blocks, but it is difficult to implement a computer. In this study, it is difficult to approximate a complex block such as a large-sized block and an affine transformation because a large amount of calculation is required in searching for a combination of similar blocks through a transformation, so a large amount of coding time is required.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.311-317
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• 2023

CT-guided percutaneous transthoracic needle biopsy (PTNB) plays a key role in the diagnosis of pulmonary abnormalities. Although the procedure is considered safe and effective, there exists a potential for complications, such as pneumothorax, hemorrhage, hemoptysis, air embolism, and tumor seeding. However, pneumatoceles after CT-guided PTNB have been rarely reported. Herein, we report two cases of pneumatoceles that developed immediately after PTNB for primary lung cancer. A pneumatocele filled with hematoma should be considered in cases with a newly developed nodule along the needle tract during short-term follow-up CT after PTNB.

• 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.