• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.6-15
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• 2012

Purpose : The objective of this study was to develop background gradient correction method using excitation pulse profile compensation for accurate fat and $T_2{^*}$ quantification in the liver. Materials and Methods: In liver imaging using gradient echo, signal decay induced by linear background gradient is weighted by an excitation pulse profile and therefore hinders accurate quantification of $T_2{^*}$and fat. To correct this, a linear background gradient in the slice-selection direction was estimated from a $B_0$ field map and signal decays were corrected using the excitation pulse profile. Improved estimation of fat fraction and $T_2{^*}$ from the corrected data were demonstrated by phantom and in vivo experiments at 3 Tesla magnetic field. Results: After correction, in the phantom experiments, the estimated $T_2{^*}$ and fat fractions were changed close to that of a well-shimmed condition while, for in vivo experiments, the background gradients were estimated to be up to approximately 120 ${\mu}T/m$ with increased homogeneity in $T_2{^*}$ and fat fractions obtained. Conclusion: The background gradient correction method using excitation pulse profile can reduce the effect of macroscopic field inhomogeneity in signal decay and can be applied for simultaneous fat and iron quantification in 2D gradient echo liver imaging.

• Investigative Magnetic Resonance Imaging
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• v.7 no.1
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• pp.12-21
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• 2003

Purpose : In order to overcome limitations in the existing conventional spectrometer, a new spectrometer with advanced functionalities is designed and implemented. Materials and Methods : We designed a spectrometer using the TMS320C6701 DSP capable of 1 giga floating point operations per second (GFLOPS). The spectrometer can generate continuously varying complicate gradient waveforms by real-time calculation, and select image plane interactively. The designed spectrometer is composed of two parts: one is DSP-based digital control part, and the other is analog part generating gradient and RF waveforms, and performing demodulation of the received RF signal. Each recover board can measure 4 channel FID signals simultaneously for parallel imaging, and provides fast reconstruction using the high speed DSP. Results : The developed spectrometer was installed on a 1.5 Tesla whole body MRI system, and performance was tested by various methods. The accurate phase control required in digital modulation and demodulation was tested, and multi-channel acquisition was examined with phase-array coil imaging. Superior image quality is obtained by the developed spectrometer compared to existing commercial spectrometer especially in the fast spin echo images. Conclusion : Interactive control of the selection planes and real-time generation of gradient waveforms are important functions required for advanced imaging such as spiral scan cardiac imaging. Multi-channel acquisition is also highly demanding for parallel imaging. In this paper a spectrometer having such functionalities is designed and developed using the TMS320C6701 DSP having 1 GFLOPS computational power. Accurate phase control was achieved by the digital modulation and demodulation techniques. Superior image qualities are obtained by the developed spectrometer for various imaging techniques including FSE, GE, and angiography compared to those obtained by the existing commercial spectrometer.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.619-625
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• 2017

The sudy was intended to evaluate the optimal equipment selection by quantitatively assessing the SNR(signal to noise ratio) and CNR(contrast to noise ratio) on the abdominal organ. This study performed on 1.5 T and 3.0 T MRI units focusing on HASTE, HASTE(f/s) and FFE(in of phase), FFE(out of phase) without using the contrast medium(Gadolinium). The data analysis was performed by randomly selecting on 1.5 T and 3.0 T abdominal MRI images. As a results, SNR and CNR values of 3.0 T is higher than 1.5 T at liver, kidney and spleen(p<0.05). Stomach, abdominal fat and pancreas was obtained a higher value at 1.5 T(p<0.05). On conclusion, the organs of outer part in the body showed generally a high value at 3.0 T, and the organs of inner part in the body including the gas showed a high value at 3.0 T because of a large difference on magnetic susceptibility.

• Korean Journal of Radiology
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• v.24 no.9
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• pp.827-837
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• 2023

Objective: To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). Materials and Methods: We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the oneweek CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC). Results: Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR]: 1.04 (1.00-1.07); P = 0.031) and RAD score (OR: 3.43 (2.34-5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75-0.89) in the training set and 0.75 (0.62-0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72-0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52-0.84) to 0.82 (0.70-0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65-0.94) (P = 0.727). Conclusion: Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.5
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• pp.628-637
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• 2004

In many drinking water treatment plants, chlorination process is one of the main techniques used for the disinfection of water. This disinfecting treatment leads to the formation of disinfection by-products (DBPs) such as haloacetonitriles (HANs), trihalomethanes (THMs), haloacetic acids (HAAs). In this study, headspace-solid phase microextraction (HS- SPME) technique was applied for the analysis of HANs in drinking water. The effects of experimental parameters such as selection of SPME fiber, the addition of salts, magnetic stirring, extraction temperature, extraction time and desorption time on the analysis were investigated. Analytical parameters such as linearity, repeatability and detection limits were also evaluated. The $50/30{\mu}m$-divinylbenzene/carboxen/polydimethylsiloxane fiber, extraction time of 30 minutes, extraction temperature of $20^{\circ}C$ and desorption time of 1 minute at $260^{\circ}C$ were the optimal experimental conditions for the analysis of HANs. The correlation coefficients ($r^2$) for HANs was 0.9979~0.9991, respectively. The relative standard deviations (%RSD) for HANs was 2.3~7.6%, respectively. Detection limits (LDs) for HANs was $0.01{\sim}0.5{\mu}g/L$, respectively.

• Journal of Welding and Joining
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• v.14 no.1
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• pp.57-67
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• 1996

With an expansion in automation of welding processes, emphasis has been shifted from other welding processes to the GMA welding. However, there is a problem with this process that the spatter occurs very frequently. In GMA welding, there are several types in the way of metal transfer from the electrode wire to the weld pool, which have a close relatonship with the spatter genetration. This study was concerned with the spatter occurring in the short-circuiting transfer. In welding with short-circuiting, the electromagnetic force formed by the welding current facilitatics the rupture of the metal bridge between the wire and workpiece and ensures the normal process of the welding process. However, the spatter can be genetrated from the droplet because of the upward magnetic force, when the droplet contacts with the weld pool. The passage of current through the bridge results in the accumulation of the thermal energy, which causes the bridge to explode in the final stage of short-circuiting, thus forming the spatter. Based on the above phenomena in conjunction with other experimental results published, the physical phenomenon related with the occurrence of spatter was modeled and the current waveform was investigated to reduce the spatter. Finally, the fuzzy rule based method was proposed to predict the time of short-circuiting and arcing in the metal transfer.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.59-64
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• 2015

IEC is an international standards which are used in many countries with Europe as the center. IEC standard is introduced in Korea according to WTO/TBT agreements, however until now there are no buildings in Korea which are designed applying IEC standard. Therefore, KEA(Korea Electric Association) is scheduled to construct Korean low voltage electrical installation integration test site which is designed applying IEC standard. In this paper, before being under construction of Korean low voltage electrical installation integration test site, power substation is modeled based on real design parameters and method to select circuit breakers and cables is presented applying IEC standard in the modeled power substation. EMTP(ElctroMagnetic Transient Program) is used for simulation program. EMTP which is power system analysis program is easy to model power system and power substation.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.670-675
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• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• Journal of Korean Neurosurgical Society
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• v.55 no.5
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• pp.261-266
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• 2014

Objective : With the increased use of interspinous spacers in the treatment of lumbar stenosis, knowledge of the geometry of the interspinous space is important. To prevent dislodgment of an interspinous spacer, the accurate depth and width of the interspinous space needs to be established to facilitate the best intraoperative selection of correct spacer size. Methods : To determine the depth and width of the interspinous space, two methods are available which utilize plain film and magnetic resonance imaging (MRI). Data analysis of the interspinous depth and width was undertaken in 100 patients. Results : The standard deviations were variable, since skin thickness (zone 1) was altered by sex and age. The difference in the zone 1 distance between adjacent interspinous processes varied according to gender (p<0.05), but was not influenced by age [p=0.32 by analysis of variance between groups (ANOVA)]. Zone 2, the supraspinous, and zone 3, the interspinous ligament depths, comprise the operative working area during insertion of an interspinous spacer. There were no differences with regard to gender or age (p>0.05). For zones 6 and 7, the interspinous distances at the narrowest and widest points, respectively, were found to decrease with the aging process, but the decrease was not statistically significant. There were no differences with regard to gender (p>0.05). Conclusion : This study provides additional information on the interspinous space. This statistical data are valuable for use in the design of interspinous spacers.

• Journal of Computing Science and Engineering
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• v.10 no.4
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• pp.118-127
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• 2016

An improved sample balanced genetic algorithm and Extreme Learning Machine (iSBGA-ELM) was designed for accurate diagnosis of Alzheimer disease (AD) and identification of biomarkers associated with AD in this paper. The proposed AD diagnosis approach uses a set of magnetic resonance imaging scans in Open Access Series of Imaging Studies (OASIS) public database to build an efficient AD classifier. The approach contains two steps: "voxels selection" based on an iSBGA and "AD classification" based on the ELM. In the first step, the proposed iSBGA searches for a robust subset of voxels with promising properties for further AD diagnosis. The robust subset of voxels chosen by iSBGA is then used to build an AD classifier based on the ELM. A robust subset of voxels keeps a high generalization performance of AD classification in various scenarios and highlights the importance of the chosen voxels for AD research. The AD classifier with maximum classification accuracy is created using an optimal subset of robust voxels. It represents the final AD diagnosis approach. Experiments with the proposed iSBGA-ELM using OASIS data set showed an average testing accuracy of 87%. Experiments clearly indicated the proposed iSBGA-ELM was efficient for AD diagnosis. It showed improvements over existing techniques.