• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.727-734
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• 2014

Digital processing technologies are being studied in various areas of image compression, recognition and recovery. However, image deterioration still occurs due to the noises in the process of image acquisition, storage and transmission. Generally in the typical noises which are included in the images, there are Gaussian noise and the mixed noise where the Gaussian noise and impulse noise are overlapped and in order to remove these noises, various researches are being executed. In order to preserve the edge and effectively remove mixed noises, image recovery filter algorithm was suggested in this study which sets and processes the adaptive weight using the median values and average values after noise judgment. Additionally, existing methods were compared through simulations and PSNR(peak signal to noise ratio) was used as a judgment standard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2167-2172
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• 2015

Due to the recent progress in information technology, demand for video imaging devices such as displays has grown. In general, images experience deterioration during the process of transmission due to various reasons. Many studies have boon undertaken on ways o reduce such noise. This paper6 suggests an algorithm that makes a judgment on the noise in order to remove the salt & pepper noise and replaces original pixels if they are non-noise while processing noise according to its density. The suggested algorithm shows a high PSNR of 30.49[dB] for Goldhill images that had been damaged of a high density salt & pepper noise(P = 60%), Compared to the exising CWMF, SWMF, and A-TMF, there were improvements by 17.74[dB], 11.52[dB], and 13.76[dB], respectively.

• Journal of Korean Neurosurgical Society
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• v.39 no.3
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• pp.198-203
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• 2006

Objective : To evaluate the natural histories and growth rates of meningiomas, the authors perform this retrospective observational study and attempt to identify those factors predicting tumor growth. Methods : Between 1993 and 2004, a total of 83 patients were diagnosed by computed tomography[CT] scans or magnetic resonance[MR] imaging as having an intracranial meningioma, and were treated by observation only using regular clinical and radiological examinations. Twenty-six of these 83 patients, with available data were included in this study. Follow up periods ranged from 9 to 137 months [mean, 55.6 mo.; median, 60 mo.]. The tumor volumes, absolute growth rates, and tumor doubling times were calculated. Results : Patient age and sex distributions were comparable to those of other studies, but exceptionally 16 meningiomas [62%] were located at the skull base in the present study. During follow-up monitoring, the majority of meningiomas grew, though 77% showed low absolute annual growth rates [$<1cm^3/yr$]. The tumor doubling times ranged from 2.87 to 201.72 years [mean, 42.91 yr]. Based on Imaging analysis, peritumoral edema and the absence of calcification were probable factors predicting tumor growth. Tumor-related symptoms seemed to be slightly related to tumor growth. Other factors, e.g., gender, age, tumor location, and T2-weighted signal Intensities on MR imaging, were not significantly related to tumor growth. Conclusion : This study shows that the majority of meningiomas are slow growing. However, variations in tumor growth are unexplained, thus individualized optimal treatment strategies should be provided in each meningioma.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2805-2810
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• 2016

Background: Differentiated thyroid cancer is the most common endocrine malignancy with a generally good prognosis. Knowing long-term outcomes of each patient helps management planning. The study was conducted to develop and validate a clinical prognostic score for predicting disease remission in patients with differentiated thyroid cancer based on patient, tumor and treatment factors. Materials and Methods: A retrospective cohort study of 1,217 differentiated thyroid cancer patients from two tertiary-care hospitals in the Northeast of Thailand was performed. Associations between potential clinical prognostic factors and remission were tested by Cox proportional-hazards analysis in 852 patients (development cohort). The prediction score was created by summation of score points weighted from regression coefficients of independent prognostic factors. Risks of disease remission were estimated and the derived score was then validated in the remaining 365 patients (validation cohort). Results: During the median follow-up time of 58 months, 648 (76.1%) patients in the development cohort had disease remission. Five independent prognostic factors were identified with corresponding score points: duration from thyroid surgery to $^{131}I$ treatment (0.721), distant metastasis at initial diagnosis (0.801), postoperative serum thyroglobulin level (0.535), anti-thyroglobulin antibodies positivity (0.546), and adequacy of serum TSH suppression (0.293). The total risk score for each patient was calculated and three categories of remission probability were proposed: ${\leq}1.628$ points (low risk, 83% remission), 1.629-1.816 points (intermediate risk, 87% remission), and ${\geq}1.817$ points (high risk, 93% remission). The concordance (C-index) was 0.761 (95% CI 0.754-0.767). Conclusions: The clinical prognostic scoring model developed to quantify the probability of disease remission can serve as a useful tool in personalized decision making regarding treatment in differentiated thyroid cancer patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.69-85
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• 2019

BeiDou navigation satellite system (BDS) is one of the four main types of global navigation satellite systems. The current system has been widely used by the military and by the aerospace, transportation, and marine fields, among others. However, challenges still remain in the BeiDou system, which requires rapid responses for delay-sensitive devices. A differential positioning algorithm called the data center-based differential positioning (DCDP) method is widely used to avoid the influence of errors. In this method, the positioning information of multiple base stations is uploaded to the data center, and the positioning errors are calculated uniformly by the data center based on the minimum variance or a weighted average algorithm. However, the DCDP method has high delay and overload risk. To solve these problems, this paper introduces edge computing to relieve pressure on the data center. Instead of transmitting the positioning information to the data center, a novel method called edge computing-based differential positioning (ECDP) chooses the nearest reference station to perform edge computing and transmits the difference value to the mobile receiver directly. Simulation results and experiments demonstrate that the performance of the ECDP outperforms that of the DCDP method. The delay of the ECDP method is about 500ms less than that of the DCDP method. Moreover, in the range of allowable burst error, the median of the positioning accuracy of the ECDP method is 0.7923m while that of the DCDP method is 0.8028m.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.609-615
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• 2020

In the modern society, the use of digital equipment is increasing along with the 4th industrial revolution, and the importance of image and signal processing is increasing. At the same time, research on noise reduction is being actively conducted. In this paper, we propose a switching filter algorithm for random-valued impulse noise cancellation. The proposed algorithm obtains the threshold value by determining the noise level present in the image, and threshold value is compared with the difference between the input pixel value and the reference value, and is used in the weight switching process of the filter. The final output of the filter is estimated by applying a pixel weight and a modified weight median filter according to the switching, and obtains a final output by comparing the estimated value with the input pixel value. To evaluate the performance of the proposed algorithm, we compared it with the existing methods using simulation and PSNR.

• Journal of Chest Surgery
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• v.56 no.6
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• pp.374-386
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• 2023

Background: The heightened morbidity and mortality associated with repeat cardiac surgery are well documented. Redo median sternotomy (MS) and minimally invasive valve surgery are options for patients with prior cardiac surgery who require mitral valve surgery (MVS). We conducted a systematic review and meta-analysis comparing the outcomes of redo MS and minimally invasive MVS (MIMVS) in this population. Methods: We searched PubMed, EMBASE, and Scopus for studies comparing outcomes of redo MS and MIMVS for MVS. To calculate risk ratios (RRs) for binary outcomes and weighted mean differences (MDs) for continuous data, we employed a random-effects model. Results: We included 12 retrospective observational studies, comprising 4157 participants (675 for MIMVS; 3482 for redo MS). Reductions in mortality (RR, 0.54; 95% confidence interval [CI], 0.37-0.80), length of hospital stay (MD, -4.23; 95% CI, -5.77 to -2.68), length of intensive care unit (ICU) stay (MD, -2.02; 95% CI, -3.17 to -0.88), and new-onset acute kidney injury (AKI) risk (odds ratio, 0.34; 95% CI, 0.19 to 0.61) were statistically significant and favored MIMVS (p<0.05). No significant differences were observed in aortic cross-clamp time, cardiopulmonary bypass time, or risk of perioperative stroke, new-onset atrial fibrillation, surgical site infection, or reoperation for bleeding (p>0.05). Conclusion: The current literature, which primarily consists of retrospective comparisons, underscores certain benefits of MIMVS over redo MS. These include decreased mortality, shorter hospital and ICU stays, and reduced AKI risk. Given the lack of high-quality evidence, prospective randomized control trials with adequate power are necessary to investigate long-term outcomes.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.2
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• pp.105-114
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• 2024

Clinical laboratories endeavor to secure quality by establishing effective quality management systems. However, laboratory environments are complex, and single quality control procedures may inadequately detect many errors. Patient-based real-time quality control (PBRTQC) is a laboratory tool that monitors the testing process using algorithms such as Bull's algorithm and several variables, such as average of normal, moving median, moving average, and exponentially weighted moving average. PBRTQC has many advantages over conventional quality control, including low cost, commutability, continuous real-time performance monitoring, and sensitivity to pre-analytical errors. However, PBRTQC is not easily implemented as it requires statistical algorithm selection, the design of appropriate rules and protocols, and performance verification. This review describes the basic concepts, methods, and procedures of PBRTQC and presents guidelines for implementing a patient-based quality management system. Furthermore, we propose the combined use of PBRTQC when the performance of internal quality control is limited. However, clinical evaluations were not conducted during this review, and thus, future evaluation is required.

• Journal of the Korean Society of Radiology
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• v.15 no.5
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• pp.591-602
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• 2021

Acute ischemic stroke(AIS) should be diagnosed within a few hours of onset of cerebral infarction symptoms using diagnostic radiology. In this study, we evaluated the clinical usefulness of SVD and the Bayesian algorithm to measure the volume of cerebral infarction using computed tomography perfusion(CTP) imaging and magnetic resonance diffusion-weighted imaging(MR DWI). We retrospectively included 50 patients (male : female = 33 : 17) who visited the emergency department with symptoms of AIS from September 2017 to September 2020. The cerebral infarct volume measured by SVD and the Bayesian algorithm was analyzed using the Wilcoxon signed rank test and expressed as a median value and an interquartile range of 25 - 75 %. The core volume measured by SVD and the Bayesian algorithm using was CTP imaging was 18.07 (7.76 - 33.98) cc and 47.3 (23.76 - 79.11) cc, respectively, while the penumbra volume was 140.24 (117.8 - 176.89) cc and 105.05 (72.52 - 141.98) cc, respectively. The mismatch ratio was 7.56 % (4.36 - 15.26 %) and 2.08 % (1.68 - 2.77 %) for SVD and the Bayesian algorithm, respectively, and all the measured values had statistically significant differences (p < 0.05). Spearman's correlation analysis showed that the correlation coefficient of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was higher than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (r = 0.915 vs. r = 0.763 ; p < 0.01). Furthermore, the results of the Bland Altman plot analysis demonstrated that the slope of the scatter plot of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was more steady than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (y = -0.065 vs. y = -0.749), indicating that the Bayesian algorithm was more reliable than SVD. In conclusion, the Bayesian algorithm is more accurate than SVD in measuring cerebral infarct volume. Therefore, it can be useful in clinical utility.

• Journal of radiological science and technology
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• v.34 no.3
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• pp.239-244
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• 2011

In this study, we evaluated diffusion weighted imaging (DWI) to investigate whether the DWI parameters can predict characteristic parameters on pathologic specimens of tumor or not. CFPAC-1 was injected subcutaneously on the back flank of athymic nude mice (n=13) then two tumors were initiated on each mouse (2${\times}$13=26 tumors). The mice were sacrificed to make specimen immediately after initial MR imaging then were compared with the MR image. A dedicated high-field (7T) small-animal MR scanner was used for image acquisitions. A T1 and T2 weighted axial image using RARE technique was acquired to measure the T2 values and tumor size. DWI MR was performed for calculating ADC values. To evaluate tumor cellularity and determine the levels of MVD, tumor cells were excised and processed for H-E staining and immunostaining using CD31. T2 values and ADC values were computed and analyzed for each half of the tumors and compared to the correlated specimens slide. Median ADC within each half of mass was compared to the cellularity and MVD in the correlated area of pathologic slide. The mean of ADC value is $0.7327{\times}10^{-3}$ $mm^2/s$ and standard deviation is $0.1075{\times}10^{-3}$ $mm^2/s$. There is a linear relationship between ADC value and tumor necrosis (R2=0.697, p< 0.001). DW image parameters including the ADC values can be utilized as surrogate markers to assess intratumoral neoangiogenesis and change of the internal structure of tumor cells.