• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1718-1733
• /
• 2023

The virtual Frisch-grid method for room-temperature radiation detectors has been widely used because of its simplicity and high performance. Recently, side electrodes were separately attached to each surface of the detectors instead of covering the entire detector surface with a single electrode. The side-electrode structure enables the measurement of the three-dimensional (3D) gamma-ray interaction in the detector. The positional information of the interaction can then be utilized to precisely calibrate the response of the detector for gamma-ray spectroscopy and imaging. In this study, we developed a 3D position-sensitive 5 × 5 × 12 mm³ cadmium-zinc-telluride (CZT) detector and applied a flattening method to correct detector responses. Collimated gamma-rays incident on the surface of the detector were scanned to evaluate the positional accuracy of the detection system. Positional distributions of the radiation interactions with the detector were imaged for quantitative and qualitative evaluation. The energy spectra of various radioisotopes were measured and improved by the detector response calibration according to the calculated positional information. The energy spectra ranged from 59.5 keV (emitted by ²⁴¹Am) to 1332 keV (emitted by ⁶⁰Co). The best energy resolution was 1.06% at 662 keV when the CZT detector was voxelized to 20 × 20 × 10.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.1
• /
• pp.1-13
• /
• 2023

Various techniques for bias correction and statistical downscaling have been developed to overcome the limitations related to the spatial and temporal resolution and error of climate change scenario data required in various applied research fields including agriculture and water resources. In this study, the characteristics of three different statistical dowscaling methods (i.e., SQM, SDQDM, and BCSA) provided by AIMS were summarized, and climate change scenarios produced by applying each method were comparatively evaluated. In order to compare the average rainfall characteristics of the past period, an index representing the average rainfall characteristics was used, and the reproducibility of extreme weather conditions was evaluated through the abnormal climate-related index. The reproducibility comparison of spatial distribution and variability was compared through variogram and pattern identification of spatial distribution using the average value of the index of the past period. For temporal reproducibility comparison, the raw data and each detailing technique were compared using the transition probability. The results of the study are presented by quantitatively evaluating the strengths and weaknesses of each method. Through comparison of statistical techniques, we expect that the strengths and weaknesses of each detailing technique can be represented, and the most appropriate statistical detailing technique can be advised for the relevant research.

• Current Optics and Photonics
• /
• v.7 no.5
• /
• pp.518-528
• /
• 2023

As an effective means of remotely detecting the spectral information of the object, the spectral calibration for the Savart polarization interference imaging spectrometer (SPIIS) is a basis and prerequisite of information quantification, and its experimental calibration scheme is firstly proposed in this paper. In order to evaluate the accuracy of the spectral information acquisition, the linear interpolation, cubic spline interpolation, and piecewise cubic interpolation algorithms are adopted, and the precision of the quadratic polynomial fitting is the highest, whose fitting error is better than 5.8642 nm in the wavelength range of [500 nm, 820 nm]. Besides, the inversed value of the spectral resolution for the monochromatic light is greater than the theoretical value, and the deviation between them becomes larger with the wavelength increasing, which is mainly caused by the structural design of the SPIIS, together with the rationality of the spectral restoration algorithm and the selection of the maximum optical path difference (OPD). This work demonstrates that the SPIIS has achieved high performance assuring the feasibility of its practical use in various fields.

• Korean Journal of Remote Sensing
• /
• v.36 no.2_1
• /
• pp.179-197
• /
• 2020

Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.

• Korean Journal of Remote Sensing
• /
• v.14 no.4
• /
• pp.376-391
• /
• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• The Journal of Korean Society for Radiation Therapy
• /
• v.20 no.1
• /
• pp.17-23
• /
• 2008

Purpose: Cone-beam CT using linear accelerator attached to on-board imager is a image guided therapy equipment. Because it is to check the patient's set-up error, correction, organ and target movement. but imaging dose should be cause of the secondary cancer when taking a image. The aim of this study is investigation of appropriate cone beam CT scan mode to compare and estimate the image quality and skin dose. Materials and Methods: Measurement by Thermoluminescence dosimeter (TLD-100, Harshaw) with using the Rando phantom are placed on each eight sites in seperately H&N, thoracic, abdominal section. each 4 methods of scan modes of are measured the for skin dose in three time. Subsequently, obtained average value. Following image quality QA protocol of equipment manufacturers using the catphan 504 phantom, image quality of each scan mode is compared and analyzed. Results: The results of the measured skin dose are described in here. The skin dose of Head & Neck are measured mode A: 8.96 cGy, mode B: 4.59 cGy, mode C: 3.46 cGy mode D: 1.76 cGy and thoracic mode A: 9.42 cGy, mode B: 4.58 cGy, mode C: 3.65 cGy, mode D: 1.85 cGy, and abdominal mode A: 9.97 cGy, mode B: 5.12 cGy, mode C: 4.03 cGy, mode D: 2.21 cGy. Approximately, dose of mode B are reduced 50%, mode C are reduced 60%, mode D are reduced 80% a point of reference dose of mode A. the results of analyzed HU reproducibility, low contrast resolution, spatial resolution (high contrast resolution), HU uniformity in evaluation item of image quality are within the tolerance value by recommended equipment manufacturer in all scan mode. Conclusion: Maintaining the image quality as well as reducing the image dose are very important in cone beam CT. In the result of this study, we are considered when to take mode A when interested in soft tissue. And we are considered to take mode D when interested in bone scan and we are considered to take mode B, C when standard scan. Increasing secondary cancer risk due to cone beam CT scan should be reduced by low mAs technique.

• Progress in Medical Physics
• /
• v.14 no.3
• /
• pp.203-210
• /
• 2003

PET (positron emission tomography) permits the investigation of physiological and biochemical processes in vivo. The accuracy of quantifying PET data is affected by its finite spatial resolution, which causes partial volume effects. In this study, we developed a method for partial volume correction using Hoffman phantom PET and MR data, and applied various FWHM (full width at half maximum) levels. We also applied this method to PET images of normal controls and tested for the possibility of clinical application. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices. The gray matter and white matter regions were then segmented into binary images. Each binary image was convolved by 4, 8, 12, 16 mm FWHM levels. These convolved images of gray and white matter were merged corresponding to the same level of FWHM. The original PET images were then divided by the convolved binary images voxel-by-voxel. These corrected PET images were multiplied by binary images. The corrected PET images were evaluated by analyzing regions of interests, which were drawn on the gray and white matter regions of the original MR image slices. We calculated the ratio of white to gray matter. We also applied this method to the PET images of normal controls. On analyzing the corrected PET images of Hoffman phantom, the ratios of the corrected images increased more than that of the uncorrected images. With the normal controls, the ratio of the corrected images increased more than that of the uncorrected images. The ratio increase of the corrected PET images was lower than that of the corrected phantom PET images. In conclusion, the method developed for partial volume correction in PET data may be clinically applied, although further study may be required for optimal correction.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.15 no.1
• /
• pp.10-16
• /
• 2011

Purpose: The partial volume effect occurs because of limit of the spatial resolution. It makes partial loss of intensity and causes SUV to be lower than it should actually be. So the purpose of this study is to calculate recovery coefficient for correcting PVE from phantom study and to compare before and after SUV correction applying to PET/CT examination. Materials and Methods: The flangeless Esser PET phantom consisting of four hot cylinders was used for this study. All of the hot cylinders were filled with FDG solution of 20.72 MBq per 1000 ml, and the phantom background was filled with FDG solution of different concentrations (33.30, 22.20, 16.65 MBq per 6440 ml) to yield H/B ratios of around 4:1, 6:1 and 8:1. Using the Biograph Truepoint 40(SIEMENS, Germany), we applied recovery coefficient method to 30 patients who were diagnosed with lung cancer after PET/CT exam. And then we analyzed and compared SUV before and after correcting partial volume effect. Results: The smaller the diameter of hot cylinder becomes, the more recovery coefficient decreased. When we applied recovery coefficient to clinical patients and compared SUV before and after correcting PVE, before the correction all lesions gave an average max SUV of 7.83. And after the correction, the average max SUV increases to 10.31. The differences in the max SUV between before and after correction were analyzed by paired t test. As a result, there were statistically significant differences (t=7.21, p=0.000). Conclusion: The SUV for quantification should be measured precisely to give consistent information of tumor uptake. But PVE is one of factors that causes SUV to be lower and to be underestimated. We can correct this PVE and calculate corrected SUV using the recovery coefficient from phantom study. And if we apply this correction method to clinical patients, we can finally assess and provide quantitative analysis more accurately.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.2
• /
• pp.63-77
• /
• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.715-727
• /
• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.