• Korean Journal of Radiology
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• v.23 no.5
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• pp.529-538
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• 2022

Objective: Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods: The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011-2013, 2014-2016, and 2017-2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not. Results: This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011-2013, 85.7% for 2014-2016, and 84.2% for 2017-2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LIRADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I² = 94.3% vs. 86.7% in sensitivity and I² = 86.6% vs. 53.2% in specificity). Conclusion: LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.

• Journal of the Korean Society of Radiology
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• v.6 no.5
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• pp.409-414
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• 2012

This study acquired molecular lmaging using nano-contrast agents, and the general condition of the same image acquisition to analyze the difference between molecular imaging and general imaging, two images are converted into DWT (Discrete Wavelet Transform). Nano-contrast agent imaging using MRI and molecular imaging using PET study of molecular imaging technology mainstream. DWT analysis of the same lesions using MRI imaging and molecular imaging block lesions are present in the lesions, illustrating the value of a high-frequency feature both highly general imaging and molecular imaging could know that. The high frequency region of the feature extraction values appear higher molecular imaging.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.434-436
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• 1999

MRI 촬상내의 체동에 의해 화상위에 나타나는 아티팩트를 제거하는 알고리즘에 관해서 기술한다. 종래의 반복적인 위상탐색법에 의한 제거법과는 달리, 위상 엔코딩 방향인 Y 방향의 체동에 대하여 MRI의 원리에 근거해서 체동과 화상의 위상공간에서의 대응관계를 해석해서 체동성분을 추출함으로써 아티팩트를 제거하는 새로운 알고리즘을 제안한다. 인체의 단층상에 있어서 피하지방 부위를 통과하는 Y방향의 한 라인상의 밀도분포는 대칭성을 갖고 있어 밀도분포위상의 선형성을 체동과 화상성분을 분리하기 위한 구속조건으로 사용한다. MRI 신호에 대해서 X 방향의 1차원 푸리에 변환을 행한 후의 Y 방향의 스펙트럼 위상값은 화상자신의 성분과 체동성분의 합이 되고 있다. Y 방향의 한 라인에 따른 밀도분포가 대칭인 경우에는 화상의 위상성분이 그 위치에 대해서 선형함수가 되고 있다. 이러한 구속조건에 근거한 아티팩트의 제거방법을 정식화하며, 시뮬레이션에 의해 본 방법의 유효성을 확인한다. 아울러, 체동 변동이 약간 큰 경우 및 Y 접선 영역의 대칭성이 무너진 경우에 대해서도 검토를 행한다.

• Proceedings of the Korean Environmental Health Society Conference
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• 2005.06a
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• pp.105-139
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• 2005

Increased signal in T1-weighted images was observed in the experimental manganese (Mn) poisoning of the non-human primate and a patient with Mn neurointoxication. However, our study showed that the increased signals in magnetic resonance images (MRI) were highly prevalent (41.6%) in Mn-exposed workers. Blood Mn concentration correlated with pallidal index. These changes in MRI tend to disappear following the withdrawal from the source of Mn accumulation, despite permanent neurological damage. Thus increased signal intensities on a T1-weighted image reflect exposure to Mn, but not necessarily manganism. Our study also showed that the concentration of Mn required to produce increased signal intensities on MRI is much lower than the threshold necessary to result in overt clinical signs of manganism. Increased signal intensities in the globus pallidus were determined by manganese accumulation in the animal experiment. Reanalysis of the previous data with the structural equation model revealed that pallidal index (Pl) on MRI reflects target organ dose of occupational Mn exposure

• Investigative Magnetic Resonance Imaging
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• v.22 no.3
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• pp.194-199
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• 2018

We present image findings, especially rare MRI of a primary breast angiosarcoma with its histopathology, and also analyze the relevant medical literature reports in terms of the MRI findings. As our patient had unique features of a primary breast angiosarcoma, this case could be very helpful for future diagnosis of this rare breast malignancy by MRI.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.343-351
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• 2022

A brain tumor forms when some tissue becomes old or damaged but does not die when it must, preventing new tissue from being born. Manually finding such masses in the brain by analyzing MRI images is challenging and time-consuming for experts. In this study, our main objective is to detect the brain's tumorous part, allowing rapid diagnosis to treat the primary disease instantly. With image processing techniques and deep learning prediction algorithms, our research makes a system capable of finding a tumor in MRI images of a brain automatically and accurately. Our tumor segmentation adopts the U-Net deep learning segmentation on the standard MICCAI BRATS 2018 dataset, which has MRI images with different modalities. The proposed approach was evaluated and achieved Dice Coefficients of 0.9795, 0.9855, 0.9793, and 0.9950 across several test datasets. These results show that the proposed system achieves excellent segmentation of tumors in MRIs using deep learning techniques such as the U-Net algorithm.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.111-115
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• 2017

Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.327-333
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• 2021

Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved. However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.

• The Journal of Churna Manual Medicine for Spine and Nerves
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• v.2 no.2
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• pp.89-104
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• 2007

Objectives : The purpose of this study is to report the image changes of four cases of Lumbar intervertebral disc Herniation after Oriental medicine Treatment Methods : We examined 4 patients with Lumbar intervertebral disc Herniation (HIVD of L-spine) who showed changes on MRI images before/after the treatment among HIVD of L-spine patients who visited Jaseng Hospital of Oriental Medicine from Jan. 2006 to Apr. 2007. Results & Conclusions : In this study, the first MRI examination of HIVD of L-spine patients was performed at the first visit and re-examination of MRI was done after the treatment. We assessed clinical symptoms by using Numerical rating scales(NRS). In each case, the size of the disc herniation was considerably reduced in MRI image. NRS was also reduced significantly.

• Korean Journal of Radiology
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• v.24 no.12
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• pp.1221-1231
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• 2023

Objective: To clinically validate the feasibility and accuracy of cine images acquired through the multitasking method, with no electrocardiogram gating and free-breathing, in measuring left ventricular (LV) function indices by comparing them with those acquired through the balanced steady-state free precession (bSSFP) method, with multiple breath-holds and electrocardiogram gating. Materials and Methods: Forty-three healthy volunteers (female:male, 30:13; mean age, 23.1 ± 2.3 years) and 36 patients requiring an assessment of LV function for various clinical indications (female:male, 22:14; 57.8 ± 11.3 years) were enrolled in this prospective study. Each participant underwent cardiac magnetic resonance imaging (MRI) using the multiple breath-hold bSSFP method and free-breathing multitasking method. LV function parameters were measured for both MRI methods. Image quality was assessed through subjective image quality scores (1 to 5) and calculation of the contrast-to-noise ratio (CNR) between the myocardium and blood pool. Differences between the two MRI methods were analyzed using the Bland-Altman plot, paired t-test, or Wilcoxon signed-rank test, as appropriate. Results: LV ejection fraction (LVEF) was not significantly different between the two MRI methods (P = 0.222 in healthy volunteers and P = 0.343 in patients). LV end-diastolic mass was slightly overestimated with multitasking in both healthy volunteers (multitasking vs. bSSFP, 60.5 ± 10.7 g vs. 58.0 ± 10.4 g, respectively; P < 0.001) and patients (69.4 ± 18.1 g vs. 66.8 ± 18.0 g, respectively; P = 0.003). Acceptable and comparable image quality was achieved for both MRI methods (multitasking vs. bSSFP, 4.5 ± 0.7 vs. 4.6 ± 0.6, respectively; P = 0.203). The CNR between the myocardium and blood pool showed no significant differences between the two MRI methods (18.89 ± 6.65 vs. 18.19 ± 5.83, respectively; P = 0.480). Conclusion: Multitasking-derived cine images obtained without electrocardiogram gating and breath-holding achieved similar image quality and accurate quantification of LVEF in healthy volunteers and patients.