• Progress in Medical Physics
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• v.24 no.4
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• pp.253-258
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• 2013

The purpose of this study is to evaluate and analyze the relationship between the external radiation dose reconstruction which is transmitted from the patient who receives radiation treatment through electronic portal imaging device (EPID) and the internal dose derived from the Monte Carlo simulation. As a comparative analysis of the two cases, it is performed to provide a basic indicator for similar studies. The geometric information of the experiment and that of the radiation source were entered into Monte Carlo n-particle (MCNPX) which is the computer simulation tool and to derive the EPID images, a tally card in MCNPX was used for visualizing and the imaging of the dose information. We set to source to surface distance (SSD) 100 cm for internal measurement and EPID. And the water phantom was set to be 100 cm of the source to surface distance (SSD) for the internal measurement and EPID was set to 90 cm of SSD which is 10 cm below. The internal dose was collected from the water phantom by using mesh tally function in MCNPX, accumulated dose data was acquired by four-portal beam exposures. At the same time, after getting the dose which had been passed through water phantom, dose reconstruction was performed using back-projection method. In order to analyze about two cases, we compared the penetrated dose by calibration of itself with the absorbed one. We also evaluated the reconstructed dose using EPID and partially accumulated (overlapped) dose in water phantom by four-portal beam exposures. The sum dose data of two cases were calculated as each 3.4580 MeV/g (absorbed dose in water) and 3.4354 MeV/g (EPID reconstruction). The result of sum dose match from two cases shows good agreement with 0.6536% dose error.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.37-43
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• 2015

Purpose $^{99m}Tc-DMSA$ renal scintigraphy serves as location, size and shape of kidney, so it has been used for diagnosis and passage observation after the operation or treatment. There are 3 methods of calculating the relative renal uptake ratio such as geometric mean of the counts from the anterior and posterior views, arithmetical mean from the only posterior view and posterior view which applied the renal depths. In this study, we seek to correlation between the change of total relative uptake ratio according to different inspection methods of obtaining the renal count rate. Materials and Methods The phantom experiments proceeded 5 times depending on each renal depth with the kidney phantom and tissue equivalent materials. In the clinical research, we investigated 36 adult patients who had visited our hospital from february to october, 2014 and received $^{99m}Tc-DMSA$ renal scan. The equipment was used as a gamma camera named INFINIA (General Electric Healthcare, milwaukee, USA) and we drew the region of interests through semiautomatic method by using Xeleris Ver. 2.1220 of GE. In addition, we obtained the lateral view of kidney to measure the renal depth of each patient. Then the results were compared with 3 methods of calculating relative renal uptake ratio. Results The phantom studies show when the difference between the left ant right kidney depth were less than 1 cm, there were no statistically significant difference among values calculated through anterior and posterior views and only posterior view (P>0.05), while the excess of 1cm, the results showed a statistically significant change in the value (P<0.05). In case of clinical research, the correlation between total relative uptake ratio by obtaining both sides of image and posterior view applied the kidney depth (r=0.999) was higher than by obtaining only posterior view and applying the kidney depth to one side image (r=0.988). Conclusion This study has found that, the difference of calculating total relative uptake ratio compared with obtaining anterior and posterior views and only posterior view. In order to reduce the error, we recommend the method of obtaining anterior and posterior views and is considered to be useful, particularly the patients have similar uptake ratio of left and right kidney and difficulties of measurements of kidney depth.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.435-445
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• 2023

A delta is a depositional landform that is formed when sediment transported by a river is deposited in a relatively low-energy environment, such as a lake, sea, or a main channel. Among these, a delta formed at the confluence of rivers has a great importance in river management and research because it has a significant impact on the hydraulic and sedimentological characteristics of the river. Recently, the equilibrium state of the confluence area has been disrupted by large-scale dredging and construction of levees in the Nakdong River. However, due to the natural recovery of the river, the confluence area is returning to its pre-dredging natural state through ongoing sedimentation. The time-series data show that the confluence delta has been steadily growing since the dredging, but once it reaches a certain size, it repeats growth and retreat, and the overall size does not change significantly. In this study, we developed a model to explain the sedimentation-erosion processes in the confluence area based on the assumption that the confluence delta reaches a dynamic equilibrium. The model is based on two fundamental principles: sedimentation due to supply from the tributary and erosion due to the main channel. The erosion coefficient that represents the Nakdong River confluence areas, was obtained using data from the tributaries of the Nakdong River. Sensitivity analyses were conducted using the developed model to understand how the confluence delta responds to changes in the sediment and water discharges of the tributary and the main channel, respectively. We then used annual average discharge of the Nakdong River's tributaries to predict the dynamic equilibrium positions of the confluence deltas. Finally, we conducted a simulation experiment on the development of the Gamcheon-Nakdong River delta using recorded daily discharge. The results showed that even though it is a simple model, it accurately predicted the dynamic equilibrium positions of the confluence deltas in the Nakdong River, including the areas where the delta had not formed, and those where the delta had already formed and predicted the trend of the response of the Gamcheon-Nakdong River delta. However, the actual retreat in the Gamcheon-Nakdong River delta was not captured fully due to errors and limitations in the simplification process. The insights through this study provide basic information on the sediment supply of the Nakdong River through the confluence areas, which can be implemented as a basic model for river maintenance and management.