• Journal of the Korean Society of Radiology
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• v.5 no.6
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• pp.401-407
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• 2011

The purpose of this study is to know the differences of MR spectra, obtained from normal volunteers by variable TE value, through the quantitative analysis of brain metabolites by peak integral and SNR between 1.5T and 3.0T, together with PRESS and STEAM pulse sequence. Single-voxel MR proton spectra of the human brain obtained from normal volunteers at both 3.0T MR system (Magnetom Trio, SIEMENS, Germany) and 1.5T MR system (Signa Twinspeed, GE, USA) using the STEAM and PRESS pulse sequence. 10 healthy volunteers (3.0T:3 males, 2 females; 1.5T : 3 males, 2 females) with the range from 22 to 30 years old (mean 26 years) participated in our study. They had no personal or familial history of neurological diseases and had a normal neurological examination. Data acquisition parameters were closely matched between the two field strengths. Spectra were recorded in the white matter of the occipital lobe. Spectra were compared in terms of resolution and signal-to-noise ratio(SNR), and echo time(TE) were estimated at both field strengths. Imaging parameters was used for acquisition of the proton spectrum were as follow : TR 2000msec, TE 30ms, 40ms, 50ms, 60ms, 90ms, 144ms, 288ms, NA=96, VOI=$20{\times}20{\times}20mm3$. As the echo times were increased, the spectra obtained from 3.0T and 1.5T show decreased peak integral and SNR at both pulse sequence. PRESS pulse sequence shows higher SNR and signal intensity than those of STEAM. Especially, Spectra in normal volunteers at 3.0T demonstrated significantly improved overall SNR and spectral resolution compared to 1.5T(Fig1). The spectra acquired at short echo time, 3T MR system shows a twice improvement in SNR compared to 1.5T MR system(Table. 1). But, there was no significant difference between 3.0Tand 1.5T at long TE It is concluded that PRESS and short TE is useful for quantification of the brain metabolites at 3.0T MRS, our standardized protocol for quantification of the brain metabolites at 3.0T MRS is useful to evaluate the brain diseases by monitoring the systematic changes of biochemical metabolites concentration in vivo.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.22-27
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• 2014

Purpose There is the recent PET/CT scan in tendency that use low dose to reduce patient's exposure along with development of equipments. We diminished $^{18}F$-FDG dose of patient to reduce patient's exposure after setting up GE Discovery 690 PET/CT scanner (GE Healthcare, Milwaukee, USA) establishment at this hospital in 2011. Accordingly, We evaluate acquisition time per proper bed by change of infusion dose to maintain quality of image of PET/CT scanner. Materials and Methods We inserted Air, Teflon, hot cylinder in NEMA NU2-1994 phantom and maintained radioactivity concentration based on the ratio 4:1 of hot cylinder and back ground activity and increased hot cylinder's concentration to 3, 4.3, 5.5, 6.7 MBq/kg, after acquisition image as increase acquisition time per bed to 30 seconds, 1 minute, 1 minute 30 seconds, 2 minute, 2 minutes 30 seconds, 3 minutes, 3 minutes 30 seconds, 4 minutes, 4 minutes 30 seconds, 5 minutes, 5 minutes 30 seconds, 10 minutes, 20 minutes, and 30 minutes, ROI was set up on hot cylinder and back radioactivity region. We computated standard deviation of Signal to Noise Ratio (SNR) and BKG (Background), compared with hot cylinder's concentration and change by acquisition time per bed, after measured Standard Uptake Value maximum ($SUV_{max}$). Also, we compared each standard deviation of $SUV_{max}$, SNR, BKG following in change of inspection waiting time (15minutes and 1 hour) by using 4.3 MBq phantom. Results The radioactive concentration per unit mass was increased to 3, 4.3, 5.5, 6.7 MBqs. And when we increased time/bed of each concentration from 1 minute 30 seconds to 30 minutes, we found that the $SUV_{max}$ of hot cylinder acquisition time per bed changed seriously according to each radioactive concentration in up to 18.3 to at least 7.3 from 30 seconds to 2 minutes. On the other side, that displayed changelessly at least 5.6 in up to 8 from 2 minutes 30 seconds to 30 minutes. SNR by radioactive change per unit mass was fixed to up to 0.49 in at least 0.41 in 3 MBqs and accroding as acquisition time per bed increased, rose to up to 0.59, 0.54 in each at least 0.23, 0.39 in 4.3 MBqs and in 5.5 MBqs. It was high to up to 0.59 from 30 seconds in radioactivity concentration 6.7 MBqs, but kept fixed from 0.43 to 0.53. Standard deviation of BKG (Background) was low from 0.38 to 0.06 in 3 MBqs and from 2 minutes 30 seconds after, low from 0.38 to 0 in 4.3 MBqs and 5.5 MBqs from 1 minute 30 seconds after, low from 0.33 to 0.05 in 6.7 MBqs at all section from 30 seconds to 30 minutes. In result that was changed the inspection waiting time to 15 minutes and 1 hour by 4.3 MBq phantoms, $SUV_{max}$ represented each other fixed values from 2 minutes 30 seconds of acquisition time per bed and SNR shown similar values from 1 minute 30 seconds. Conclusion As shown in the above, when we increased radioactive concentration per unit mass by 3, 4.3, 5.5, 6.7 MBqs, the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the same way, in the change of inspection waiting time (15 minutes and 1 hour), we could find that the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the result of this NEMA NU2-1994 phantom experiment, we found that the minimum acquisition time per bed was 2 minutes 30 seconds for evaluating values of fixed $SUV_{max}$ and SNR even in change of inserting radioactive concentration. However, this acquisition time can be different according to features and qualities of equipment.