• The Korean Journal of Nuclear Medicine Technology
• /
• v.13 no.3
• /
• pp.102-109
• /
• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• Journal of the Korean Society of Radiology
• /
• v.10 no.8
• /
• pp.597-602
• /
• 2016

Recent clinical field utilizes the aluminium filter in order to reduce the low-energy photons. However, the usage of the filter can cause adverse effect on the image quality because of the scattered dose that is generated by X-ray hardening phenomenon. Further, usage of filter with improper thickness can be a reason of dose creep phenomenon where unnecessary exposure is generated towards the patient. In this study, the author evaluated the RMS and the RSD analysis in order to have a quantitative evaluation for the effect of forward scattering dose by the filter on the image. as a result of the study, the FSR and the RSD was increased together with the increasing of thickness of the filter. In this study the RSD means the standard deviation of the mean value is relatively size. It can be understood that the signal-to-noise ratio decreases when the average value is taken as a signal and the standard deviation is judged as a noise. The signal-to-noise ratio can understanding as index of resolution at image. Based on these findings, it was quantitatively verified that there is a correlation of the image quality with the FSR by using an additional filter. The results, a 2.5 mmAl which is as recommended by NCRP in the tube voltage of 70 kVp or more showed the 14.6% on the RSD when the filter was not in used. these results are considered able to be utilized as basic data for the study about the filter to improve the quality of the image.

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

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.38 no.3
• /
• pp.181-189
• /
• 2002

This paper describes the positioning accuracies for single and multiple reference stations at fixed stations in Yosu harbor and Pukyong National University in the south coast of Korea from Jan. to Oct. 2001. Also we observed the change of positioning accuracy during a day and the available range of the DGPS reference station. he results obtained are main summarized as follows; 1. With single DGPS reference station, 2drms and the average positioning .error were 5.6m, 7.3m respectively. Measurement positions indicated an incline toward one way away from the actual position. 2. With multiple DGPS reference stations, 2drms and the average position error were 5.5m, 3.2m for the arithmetic mean, respectively. They were 5.3m, 3.8m for the weighted average, respectively. As far as the separation between the user and the reference station, using multiple reference stations improved position accuracy more than using single reference station. 3. The average positioning error increased between 16: 00 and 22 : 00. The average number of observed satellite and HDOP were 7.1m, 0.49 respectively. 4. Coverage of DGPS reference stations in the south coast of Korea was estimated to be 110nm. Signal strength and signal to noise ratio was not available the DGPS signal below 19㏈, 8㏈ respectively.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.1
• /
• pp.9-18
• /
• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.