• Title/Summary/Keyword: Accuracy comparison

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Mapping Mammalian Species Richness Using a Machine Learning Algorithm (머신러닝 알고리즘을 이용한 포유류 종 풍부도 매핑 구축 연구)

  • Zhiying Jin;Dongkun Lee;Eunsub Kim;Jiyoung Choi;Yoonho Jeon
    • Journal of Environmental Impact Assessment
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    • v.33 no.2
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    • pp.53-63
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    • 2024
  • Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

Dimensional Quality Assessment for Assembly Part of Prefabricated Steel Structures Using a Stereo Vision Sensor (스테레오 비전 센서 기반 프리팹 강구조물 조립부 형상 품질 평가)

  • Jonghyeok Kim;Haemin Jeon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.3
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    • pp.173-178
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    • 2024
  • This study presents a technique for assessing the dimensional quality of assembly parts in Prefabricated Steel Structures (PSS) using a stereo vision sensor. The stereo vision system captures images and point cloud data of the assembly area, followed by applying image processing algorithms such as fuzzy-based edge detection and Hough transform-based circular bolt hole detection to identify bolt hole locations. The 3D center positions of each bolt hole are determined by correlating 3D real-world position information from depth images with the extracted bolt hole positions. Principal Component Analysis (PCA) is then employed to calculate coordinate axes for precise measurement of distances between bolt holes, even when the sensor and structure orientations differ. Bolt holes are sorted based on their 2D positions, and the distances between sorted bolt holes are calculated to assess the assembly part's dimensional quality. Comparison with actual drawing data confirms measurement accuracy with an absolute error of 1mm and a relative error within 4% based on median criteria.

Microbial Forensics: Comparison of MLVA Results According to NGS Methods, and Forensic DNA Analysis Using MLVA (미생물법의학: 차세대염기서열분석 방법에 따른 MLVA 결과 비교 및 이를 활용한 DNA 감식)

  • Hyeongseok Yun;Seungho Lee;Seunghyun Lim;Daesang Lee;Sehun Gu;Jungeun Kim;Juhwan Jeong;Seongjoo Kim;Gyeunghaeng Hur;Donghyun Song
    • Journal of the Korea Institute of Military Science and Technology
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    • v.27 no.4
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    • pp.507-515
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    • 2024
  • Microbial forensics is a scientific discipline for analyzing evidence related to biological crimes by identifying the origin of microorganisms. Multiple locus variable number tandem repeat analysis(MLVA) is one of the microbiological analysis methods used to specify subtypes within a species based on the number of tandem repeat in the genome, and advances in next generation sequencing(NGS) technology have enabled in silico anlysis of full-length whole genome sequences. In this paper, we analyzed unknown samples provided by Robert Koch Institute(RKI) through The United Nations Secretary-General's Mechanism(UNSGM)'s external quality assessment exercise(EQAE) project, which we officially participated in 2023. We confirmed that the 3 unknown samples were B. anthracis through nucleic acid isolation and genetic sequence analysis studies. MLVA results on 32 loci of B. anthracis were analysed by using genome sequences obtained from NGS(NextSeq and MinION) and Sanger sequencing. The MLVA typing using short-reads based NGS platform(NextSeq) showed a high probability of causing assembly error when a size of the tandem repeats was grater than 200 bp, while long-reads based NGS platform(MinION) showed higher accuracy than NextSeq, although insertion and deletion was observed. We also showed hybrid assembly can correct most indel error caused by MinION. Based on the MLVA results, genetic identification was performed compared to the 2,975 published MLVA databases of B. anthracis, and MLVA results of 10 strains were identical with 3 unkonwn samples. As a result of whole genome alignment of the 10 strains and 3 unknown samples, all samples were identified as B. anthracis strain A4564 which is associated with injectional anthrax isolates in heroin users.

Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging for Language Mapping in Brain Tumor Surgery: Validation With Direct Cortical Stimulation and Cortico-Cortical Evoked Potential

  • Koung Mi Kang;Kyung Min Kim;In Seong Kim;Joo Hyun Kim;Ho Kang;So Young Ji;Yun-Sik Dho;Hyongmin Oh;Hee-Pyoung Park;Han Gil Seo;Sung-Min Kim;Seung Hong Choi;Chul-Kee Park
    • Korean Journal of Radiology
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    • v.24 no.6
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    • pp.553-563
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    • 2023
  • Objective: Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging-derived tractography (DTI-t) contribute to the localization of language areas, but their accuracy remains controversial. This study aimed to investigate the diagnostic performance of preoperative fMRI and DTI-t obtained with a simultaneous multi-slice technique using intraoperative direct cortical stimulation (DCS) or corticocortical evoked potential (CCEP) as reference standards. Materials and Methods: This prospective study included 26 patients (23-74 years; male:female, 13:13) with tumors in the vicinity of Broca's area who underwent preoperative fMRI and DTI-t. A site-by-site comparison between preoperative (fMRI and DTI-t) and intraoperative language mapping (DCS or CCEP) was performed for 226 cortical sites to calculate the sensitivity and specificity of fMRI and DTI-t for mapping Broca's areas. For sites with positive signals on fMRI or DTI-t, the true-positive rate (TPR) was calculated based on the concordance and discordance between fMRI and DTI-t. Results: Among 226 cortical sites, DCS was performed in 100 sites and CCEP was performed in 166 sites. The specificities of fMRI and DTI-t ranged from 72.4% (63/87) to 96.8% (122/126), respectively. The sensitivities of fMRI (except for verb generation) and DTI-t were 69.2% (9/13) to 92.3% (12/13) with DCS as the reference standard, and 40.0% (16/40) or lower with CCEP as the reference standard. For sites with preoperative fMRI or DTI-t positivity (n = 82), the TPR was high when fMRI and DTI-t were concordant (81.2% and 100% using DCS and CCEP, respectively, as the reference standards) and low when fMRI and DTI-t were discordant (≤ 24.2%). Conclusion: fMRI and DTI-t are sensitive and specific for mapping Broca's area compared with DCS and specific but insensitive compared with CCEP. A site with a positive signal on both fMRI and DTI-t represents a high probability of being an essential language area.

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels

  • Pyeong Hwa Kim;Hee Mang Yoon;Jeong Rye Kim;Jae-Yeon Hwang;Jin-Ho Choi;Jisun Hwang;Jaewon Lee;Jinkyeong Sung;Kyu-Hwan Jung;Byeonguk Bae;Ah Young Jung;Young Ah Cho;Woo Hyun Shim;Boram Bak;Jin Seong Lee
    • Korean Journal of Radiology
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    • v.24 no.11
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    • pp.1151-1163
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    • 2023
  • Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

Development and Validation of 18F-FDG PET/CT-Based Multivariable Clinical Prediction Models for the Identification of Malignancy-Associated Hemophagocytic Lymphohistiocytosis

  • Xu Yang;Xia Lu;Jun Liu;Ying Kan;Wei Wang;Shuxin Zhang;Lei Liu;Jixia Li;Jigang Yang
    • Korean Journal of Radiology
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    • v.23 no.4
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    • pp.466-478
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    • 2022
  • Objective: 18F-fluorodeoxyglucose (FDG) PET/CT is often used for detecting malignancy in patients with newly diagnosed hemophagocytic lymphohistiocytosis (HLH), with acceptable sensitivity but relatively low specificity. The aim of this study was to improve the diagnostic ability of 18F-FDG PET/CT in identifying malignancy in patients with HLH by combining 18F-FDG PET/CT and clinical parameters. Materials and Methods: Ninety-seven patients (age ≥ 14 years) with secondary HLH were retrospectively reviewed and divided into the derivation (n = 71) and validation (n = 26) cohorts according to admission time. In the derivation cohort, 22 patients had malignancy-associated HLH (M-HLH) and 49 patients had non-malignancy-associated HLH (NM-HLH). Data on pretreatment 18F-FDG PET/CT and laboratory results were collected. The variables were analyzed using the Mann-Whitney U test or Pearson's chi-square test, and a nomogram for predicting M-HLH was constructed using multivariable binary logistic regression. The predictors were also ranked using decision-tree analysis. The nomogram and decision tree were validated in the validation cohort (10 patients with M-HLH and 16 patients with NM-HLH). Results: The ratio of the maximal standardized uptake value (SUVmax) of the lymph nodes to that of the mediastinum, the ratio of the SUVmax of bone lesions or bone marrow to that of the mediastinum, and age were selected for constructing the model. The nomogram showed good performance in predicting M-HLH in the validation cohort, with an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.686-0.971). At an appropriate cutoff value, the sensitivity and specificity for identifying M-HLH were 90% (9/10) and 68.8% (11/16), respectively. The decision tree integrating the same variables showed 70% (7/10) sensitivity and 93.8% (15/16) specificity for identifying M-HLH. In comparison, visual analysis of 18F-FDG PET/CT images demonstrated 100% (10/10) sensitivity and 12.5% (2/16) specificity. Conclusion: 18F-FDG PET/CT may be a practical technique for identifying M-HLH. The model constructed using 18F-FDG PET/CT features and age was able to detect malignancy with better accuracy than visual analysis of 18F-FDG PET/CT images.

Coronary Computed Tomography Angiography for the Diagnosis of Vasospastic Angina: Comparison with Invasive Coronary Angiography and Ergonovine Provocation Test

  • Jiesuck Park;Hyung-Kwan Kim;Eun-Ah Park;Jun-Bean Park;Seung-Pyo Lee;Whal Lee;Yong-Jin Kim;Dae-Won Sohn
    • Korean Journal of Radiology
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    • v.20 no.5
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    • pp.719-728
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    • 2019
  • Objective: To investigate the diagnostic validity of coronary computed tomography angiography (cCTA) in vasospastic angina (VA) and factors associated with discrepant results between invasive coronary angiography with the ergonovine provocation test (iCAG-EPT) and cCTA. Materials and Methods: Of the 1397 patients diagnosed with VA from 2006 to 2016, 33 patients (75 lesions) with available cCTA data from within 6 months before iCAG-EPT were included. The severity of spasm (% diameter stenosis [%DS]) on iCAGEPT and cCTA was assessed, and the difference in %DS (Δ%DS) was calculated. Δ%DS was compared after classifying the lesions according to pre-cCTA-administered sublingual nitroglycerin (SL-NG) or beta-blockers. The lesions were further categorized with %DS ≥ 50% on iCAG-EPT or cCTA defined as a significant spasm, and the diagnostic performance of cCTA on identifying significant spasm relative to iCAG-EPT was assessed. Results: Compared to lesions without SL-NG treatment, those with SL-NG treatment showed a higher Δ%DS (39.2% vs. 22.1%, p = 0.002). However, there was no difference in Δ%DS with or without beta-blocker treatment (35.1% vs. 32.6%, p = 0.643). The significant difference in Δ%DS associated with SL-NG was more prominent in patients who were aged < 60 years, were male, had body mass index < 25 kg/m2, and had no history of hypertension, diabetes, or dyslipidemia. Based on iCAG-EPT as the reference, the per-lesion-based sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of cCTA for VA diagnosis were 7.5%, 94.0%, 60.0%, 47.1%, and 48.0%, respectively. Conclusion: For patients with clinically suspected VA, confirmation with iCAG-EPT needs to be considered without completely excluding the diagnosis of VA simply based on cCTA results, although further prospective studies are required for confirmation.

Comparison of Monoexponential, Biexponential, Stretched-Exponential, and Kurtosis Models of Diffusion-Weighted Imaging in Differentiation of Renal Solid Masses

  • Jianjian Zhang;Shiteng Suo;Guiqin Liu;Shan Zhang;Zizhou Zhao;Jianrong Xu;Guangyu Wu
    • Korean Journal of Radiology
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    • v.20 no.5
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    • pp.791-800
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    • 2019
  • Objective: To compare various models of diffusion-weighted imaging including monoexponential apparent diffusion coefficient (ADC), biexponential (fast diffusion coefficient [Df], slow diffusion coefficient [Ds], and fraction of fast diffusion), stretched-exponential (distributed diffusion coefficient and anomalous exponent term [α]), and kurtosis (mean diffusivity and mean kurtosis [MK]) models in the differentiation of renal solid masses. Materials and Methods: A total of 81 patients (56 men and 25 women; mean age, 57 years; age range, 30-69 years) with 18 benign and 63 malignant lesions were imaged using 3T diffusion-weighted MRI. Diffusion model selection was investigated in each lesion using the Akaike information criteria. Mann-Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. Results: Goodness-of-fit analysis showed that the stretched-exponential model had the highest voxel percentages in benign and malignant lesions (90.7% and 51.4%, respectively). ADC, Ds, and MK showed significant differences between benign and malignant lesions (p < 0.05) and between low- and high-grade clear cell renal cell carcinoma (ccRCC) (p < 0.05). α was significantly lower in the benign group than in the malignant group (p < 0.05). All diffusion measures showed significant differences between ccRCC and non-ccRCC (p < 0.05) except Df and α (p = 0.143 and 0.112, respectively). α showed the highest diagnostic accuracy in differentiating benign and malignant lesions with an area under the ROC curve of 0.923, but none of the parameters from these advanced models revealed significantly better performance over ADC in discriminating subtypes or grades of renal cell carcinoma (RCC) (p > 0.05). Conclusion: Compared with conventional diffusion parameters, α may provide additional information for differentiating benign and malignant renal masses, while ADC remains the most valuable parameter for differentiation of RCC subtypes and for ccRCC grading.

Retrospective Electrocardiography-Gated Real-Time Cardiac Cine MRI at 3T: Comparison with Conventional Segmented Cine MRI

  • Chen Cui;Gang Yin;Minjie Lu;Xiuyu Chen;Sainan Cheng;Lu Li;Weipeng Yan;Yanyan Song;Sanjay Prasad;Yan Zhang;Shihua Zhao
    • Korean Journal of Radiology
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    • v.20 no.1
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    • pp.114-125
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    • 2019
  • Objective: Segmented cardiac cine magnetic resonance imaging (MRI) is the gold standard for cardiac ventricular volumetric assessment. In patients with difficulty in breath-holding or arrhythmia, this technique may generate images with inadequate quality for diagnosis. Real-time cardiac cine MRI has been developed to address this limitation. We aimed to assess the performance of retrospective electrocardiography-gated real-time cine MRI at 3T for left ventricular (LV) volume and mass measurement. Materials and Methods: Fifty-one patients were consecutively enrolled. A series of short-axis cine images covering the entire left ventricle using both segmented and real-time balanced steady-state free precession cardiac cine MRI were obtained. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and LV mass were measured. The agreement and correlation of the parameters were assessed. Additionally, image quality was evaluated using European CMR Registry (Euro-CMR) score and structure visibility rating. Results: In patients without difficulty in breath-holding or arrhythmia, no significant difference was found in Euro-CMR score between the two techniques (0.3 ± 0.7 vs. 0.3 ± 0.5, p > 0.05). Good agreements and correlations were found between the techniques for measuring EDV, ESV, EF, SV, and LV mass. In patients with difficulty in breath-holding or arrhythmia, segmented cine MRI had a significant higher Euro-CMR score (2.3 ± 1.2 vs. 0.4 ± 0.5, p < 0.001). Conclusion: Real-time cine MRI at 3T allowed the assessment of LV volume with high accuracy and showed a significantly better image quality compared to that of segmented cine MRI in patients with difficulty in breath-holding and arrhythmia.

Comparison of Esophageal Cancer Radiation Therapy Plans Using Volumetric Modulated Arc Therapy (체적 조절 호형 방사선치료(VMAT)를 활용한 식도암 치료계획 비교)

  • Won-Young Jeong;Jae-Bok Han;Young-Hyun Seo;Jong-Nam Song
    • Journal of the Korean Society of Radiology
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    • v.18 no.3
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    • pp.249-256
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    • 2024
  • The study aimed to evaluate the efficacy of treatment plans using full Arc and Partial Arc Coplanar volumetric modulated arc therapy and Non-Coplanar volumetric modulated arc therapy to minimize radiation treatment side effects, such as pneumonia, and protect normal organs in esophageal cancer radiotherapy. 30 patients who underwent Concurrent Chemoradiotherapy for esophageal cancer were included. Compared planning target volume, lung, heart, spinal cord and total monitor units among three treatment plans: fVMAT(2 Full Arc), pVMAT(4 Partial Arc), and ncVMAT(2 Partial Arc + 2 Non-Coplanar Arc). All plans met the PTV criteria, showing uniform distribution. The average dose to the heart was 5.8 Gy for fVMAT, 6.97 Gy for pVMAT, and 7.6 Gy for ncVMAT, with the lowest value in fVMAT, which was statistically significant. However, the average lung dose was 9.01 Gy for fVMAT, 7.71 Gy for pVMAT, and 7.12 Gy for ncVMAT, with V5Gy(%) values of 52.22%, 38.61%, 36.35% and V10Gy(%) values of 37.8%, 27.33%, 24.15% respectively. ncVMAT showed the lowest values, while fVMAT had the highest, with statistical significance. In conclusion, ncVMAT effectively reduces lung radiation exposure in esophageal cancer radiotherapy, potentially reducing the incidence of side effects such as pneumonia. However, considering factors like setup accuracy and treatment time, applying an appropriate treatment plan may lead to better outcomes.