• 한국의학물리학회지:의학물리
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• 제14권2호
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• pp.131-140
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• 2003

3차원 영상의 해부학 구조에 대한 정확한 거리 측정은 중요한 역할을 하고 있으므로, 인체 두개골 팬텀을 사용하여 다검출기 CT에서의 슬라이스 두께별 획득 변수에 따른 3차원 영상의 정량적 특성에 관하여 거리 측정방법에 의한 정확도 평가를 실시하였다. 두개골 팬텀의 외부에 임상적으로 중요한 의미를 갖는 21 개의 위치를 표시하고 각 점간의 거리를 실측하였다. 실측한 데이터는 3차원 재구성 영상의 계측값과 비교평가 하기 위한 기준으로 삼았다. 다검출기 CT를 사용하여 200 mA, 120 kVp의 X-선 튜브 조건과 갠트리 회전 당 스캔(scan) 시간 1초로 단면영상을 획득하였다. 축형 모드와 나선형 모드(pitch 3:1, 6:1)에서 각각 1.25 mm, 2.50 mm, 3.75 mm, 5.00 mm의 슬라이스 두께로 획득하였고, 나선형 모드에서 획득된 단면영상을 다시 1.25 mm로 획득하였다. 영상분석 소프트웨어를 이용하여 3차원 영상 재구성 및 거리측정을 하고 통계분석을 실시하였다. 1.25 mm, 2.50 mm, 3.75 mm, 5.00 mm의 계측값의 정확도는 각각 48%, 33%, 23%, 14%로 나타났으며 1.25 mm로 재구성한 3차원 영상의 정확도는 각각 53%, 41%, 43%, 36%로 나타났다. 그러나, 1.25 mm로 재구성한 3차원영상들 간의 거리측정의 정확도 사이에서 통계적으로 유의할 만한 수준(P-value<0.05)의 차이는 보이지 않았다. 다검출기 CT의 영상획득 변수에 따른 3차원 재구성 영상에서의 각 점간의 거리측정 결과는 피치나 스캔 모드에서 보다 슬라이스 두께와 재구성 슬라이스 두께에 따른 영향이 더욱 크다는 것을 나타내었다.

• 대기
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• 제24권3호
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• pp.365-378
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• 2014

The limits of S-band dual-polarization radars in Korea are not reflected on the recent weather forecasts of Korea Meteorological Administration and furthermore, they are only utilized for rainfall estimations and hydrometeor classification researches. Therefore, this study applied four merging methods [SA (Simple Average), WA (Weighted Average), SSE (Sum of Squared Error), TV (Time-varying mergence)] to the QPE (Quantitative Precipitation Estimation) model [called RAR (Radar-AWS Rainfall) calculation system] using single-polarization radars and S-band dual-polarization radar in order to improve the accuracy of the rainfall estimation of the RAR calculation system. As a result, the merging results of the WA and SSE methods, which are assigned different weights due to the accuracy of the individual model, performed better than the popular merging method, the SA (Simple Average) method. In particular, the results of TVWA (Time-Varying WA) and TVSSE (Time-Varying SSE), which were weighted differently due to the time-varying model error and standard deviation, were superior to the WA and SSE. Among of all the merging methods, the accuracy of the TVWA merging results showed the best performance. Therefore, merging the rainfalls from the RAR calculation system and S-band dual-polarization radar using the merging method proposed by this study enables to improve the accuracy of the quantitative rainfall estimation of the RAR calculation system. Moreover, this study is worthy of the fundamental research on the active utilization of dual-polarization radar for weather forecasts.

• Asian-Australasian Journal of Animal Sciences
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• 제18권12호
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• pp.1669-1674
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• 2005

Maximum likelihood methodology was applied to analyze the efficiency and statistical power of interval mapping by using a threshold model. The factors that affect QTL detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the size of segregating population is 500. The results showed that the threshold model has a great advantage in parameters estimation and power of QTL mapping, and has nice efficiency and accuracy for discrete traits. In addition, the accuracy and power of QTL mapping depended on the effect of putative quantitative trait loci, the value of heritability and incidence directly. With the increase of QTL effect, heritability and incidence of categories, the accuracy and power of QTL mapping improved correspondingly.

• 핵의학기술
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• 제28권1호
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• pp.57-69
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• 2024

Purpose: Quantitative analysis through count measurement in nuclear medicine planar images is limited by analysis techniques that are useful for obtaining various clinical information or by organ overlap or artifacts in actual clinical practice. On the other hand, the use of SPECT tomography images is quantitative analysis using volume rather than planar, which is not only free from problems such as projection overlap, but also has excellent quantitative accuracy. In the use of developing SPECT quantitative analysis technology, this study aims to compare the accuracy of quantitative analysis between ROI of the conventional planar images and VOI of the SPECT tomographic images in evaluating the count change happened by the volume change of the source. Materials and Methods: A ^99mTcO₄^- source(200.17 MBq) was filled with sterilized water in the syringe to create a phantom with an inner diameter volume of 60 cc, and a planar image and a SPECT image were obtained by reducing the volume by 15 cc (25%) respectively. ROI and VOI(threshold: 1~45%, 5% interval) were set for each image obtained to estimate true count and measure the total count, and compared with the preseted volumetric change rate(%). Results: When volume changes of 25%, 50%, and 75% occurred in the initial volume of 60 cc(100%) of the phantom, the average count changes of the measured planar image were 26.8%, 53.2%, 77.5%, and the average count changes of the SPECT image were 24.4%, 50.9%, and 76.8%. In this case, the VOI size(cm³) set showed an average change rate of 25.4%, 51.1%, and 76.6%. The highest threshold value for the accuracy of radioactive concentration by VOI size (average error -1.03%) was 35%, and the VOI size of the same threshold had an error of -17.1% on average compared to the actual volume. Conclusion: On average, the count-based volumetric change rate in nuclear medicine images was able to track changes more accurately using VOI than ROI, but there was no significant difference with relatively similar value. However, the accuracy of radioactive concentration according to individual VOI sizes did not match, but it is considered that a relatively accurate quantitative analysis can be expected when the size of VOI is set smaller than the actual volume.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.293-294
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• 2010

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• 한국수자원학회논문집
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• 제50권5호
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• pp.335-346
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• 2017

본 연구에서는 공간규모분할 기법(SCDM)을 적용하여 레이더 예측강우를 산정하고, 도시홍수예보 관점에서 기상청 현업 레이더 예측강우(MAPLE 및 KONOS)와 함께 수문학적 활용성을 평가하였다. 본 연구에서 제시한 공간규모분할 기법은 강우를 층운형과 대류성 강우로 분리하여 각각의 이동속도를 고려하여 개별예측 및 재합성하는 것이다. 수도권 영역의 세 호우 사례를 대상으로 기상청 MAPLE 및 KONOS와의 예측강우 정확도를 평가한 결과, 본 연구에서 적용한 예측기법은 기법의 단순함에 비해 양호한 예측 정확도를 보였다. 또한, 강남유역을 대상으로 각 예측강우의 수심모의 정확도를 평가한 결과, MAPLE 및 SCDM에 비하여 KONOS가 첨두수심을 보다 정확하게 모의하였으나, 호우의 시간적 패턴 구현의 정확도가 높지 않았다. SCDM의 경우 정량적인 오차는 다소 크게 나타났지만, 전체적으로 관측수심과 유사한 모의 양상을 보였다. 추후 부족한 정량적 정확도를 보정 기법 및 수치예보자료와의 결합을 통해 개선한다면 SCDM의 예측강우가 홍수예보를 위한 입력자료로 유용하게 활용될 수 있을 것으로 판단된다.

• Asian Pacific Journal of Cancer Prevention
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• 제14권11호
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• pp.6331-6335
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• 2013

Objective:To evaluate the performance of combined quantitative analysis of thyroid blood flow and static imaging data in the differential diagnosis of thyroid nodules. Method: Thyroid blood flow and static imaging were performed in 165 patients with thyroid nodules. Patients were divided into a benign thyroid nodule group (BTN, n=135) and a malignant thyroid nodule group (MTN, n=30) based on the results of post-surgical pathologic examination. Carotid artery thyroid transit times (CTTT), perfusion ratio of thyroid nodule blood/thyroid blood (TNB/TB), and perfusion ratio of thyroid nodule blood/carotid artery blood (TNB/CAB) were measured using thyroid blood flow imaging. The ratios between thyroid nodule and ipsilateral submandibular gland (TN/SG) and thyroid nodule and normal thyroid tissue (TN/T) were measured from thyroid static imaging. The differences between the BTN and MTN groups were compared. Results: 1) CTTT was markedly lower in the MTN group than the BTN group, the difference being statistically significant. 2) TNB/TB and TNB/CAB were both significantly higher in MTN than BTN groups. 3) TN/T was significantly lower in MTN group than BTN group. 4) TN/SG was lower in MTN group than BTN group, but the difference was not statistically significant. 5) Using the combination of CTTT and TN/T, the sensitivity, specificity and accuracy were 93.1%, 95.3% and 94.9% respectively for the diagnosis of MTN. Using the combination of CTTT, TNB/TB and TN/T, the sensitivity, specificity and accuracy changed to 89.7%, 100%, and 98.1% respectively. 6) Correlation analysis demonstrated a significant correlation between TN/T and TNB/TB (r=-0.384, P=0.036) and TNB/CAB (r=-0.466, P=0.009) in the MTN group. Conclusion: The combination of quantitative markers from thyroid blood flow and thyroid static imaging had high specificity and accuracy in differential diagnosis of benign and malignant thyroid nodules, thus providing an important imaging diagnostic approach.

• 한국산업융합학회 논문집
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• 제26권4_2호
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• pp.669-678
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• 2023

Recently, spatial information has been applied to various fields and its usability is increasing day by day. In particular, in the field of civil engineering and construction, BIM based on spatial information is being applied to all construction industries and related research has been conducted. BIM is a technology that utilizes spatial information from the design phase and aids in the construction and maintenance of buildings, including the management of their attributes. However, to apply BIM technology to existing buildings, it takes a lot of time and money to produce models based on design drawings along with current surveying. In this study, quantitative and qualitative analysis was conducted to determine the applicability of the acquired data and the applicability of BIM by generating data and analyzing the accuracy using UAV images and ground lidar, which are representative spatial information acquisition methods. Quantitative analysis revealed that TLS (Terrestrial Laser Scanner) showed reliable accuracy in both planar and elevation measurements, whereas unmanned aerial images exhibited lower accuracy in elevation measurements, resulting in reduced reliability. Qualitative analysis indicated that neither TLS nor unmanned aerial images alone provided perfect completeness. However, the combination of both spatial information sources, tailored to specific needs, resulted in the most comprehensive completeness. Therefore, it is concluded that the appropriate utilization of spatial information acquired through unmanned aerial images and TLS holds the potential for application in the fields of BIM and reverse engineering.

• 대한방사선기술학회지:방사선기술과학
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• 제46권6호
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• pp.535-542
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• 2023

This study aimed to implement a deep learning model that can perform quantitative quality control through ACTS software used for quantitative evaluation of ACR phantom in CT quality control and evaluate its usefulness. By changing the scanning conditions, images of three modules of the ACR phantom's slice thickness (ST), low contrast resolution (LC), and high contrast resolution (HC) were obtained and classified as ACTS software. The deep learning model used ResNet18, implementing three models in which ST, HC, and LC were learned with epoch 50 and an integrated model in which three modules were learned with Epoch 10, 30, and 50 at once. The performance of each model was evaluated through Accuracy and Loss. When comparing and evaluating the accuracy and loss function values of the deep learning models by ST, LC, and HC modules, the Accuracy and Loss of the HC model were the best with 100% and 0.0081, and in the integrated model according to the Epoch value, Accuracy and Loss with epoch 50 were the best with 96.29% and 0.1856. This paper showed that quantitative quality control is possible through a deep learning model, and it can be used as a basis and evidence for applying deep learning to the CT quality control.