• Imaging Science in Dentistry
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• v.51 no.3
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• pp.237-242
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• 2021

Purpose: The aim of this study was to analyse and review deep learning convolutional neural networks for detecting and diagnosing early-stage dental caries on periapical radiographs. Materials and Methods: In order to conduct this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA) guidelines were followed. Studies published from 2015 to 2021 under the keywords(deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed. Results: When dental caries is improperly diagnosed, the lesion may eventually invade the enamel, dentin, and pulp tissue, leading to loss of tooth function. Rapid and precise detection and diagnosis are vital for implementing appropriate prevention and treatment of dental caries. Radiography and intraoral images are considered to play a vital role in detecting dental caries; nevertheless, studies have shown that 20% of suspicious areas are mistakenly diagnosed as dental caries using this technique; hence, diagnosis via radiography alone without an objective assessment is inaccurate. Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. Conclusion: Clinical applications of deep learning convolutional neural networks in the dental field have shown significant accuracy in detecting and diagnosing dental caries, and these models hold promise in supporting dental practitioners to improve patient outcomes.

• Imaging Science in Dentistry
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• v.50 no.4
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• pp.291-298
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• 2020

Purpose: The detection and exact localization of penetrating foreign bodies are crucial for the appropriate management of patients with dentoalveolar trauma. This study compared the efficacy of cone-beam computed tomography (CBCT) and spiral computed tomography (CT) scans for the detection of different foreign bodies composed of 5 frequently encountered materials in 2 sizes. The effect of the location of the foreign bodies on their visibility was also analyzed. Materials and Methods: In this in vitro study, metal, tooth, stone, glass, and plastic particles measuring 1×1×1 mm and 2×2×2 mm were prepared. They were implanted in a sheep's head in the tongue muscle, nasal cavity, and at the interface of the mandibular cortex and soft tissue. CBCT and spiral CT scans were taken and the visibility of foreign bodies was scored by 4 skilled maxillofacial radiologists who were blinded to the location and number of foreign bodies. Results: CT and CBCT were equally accurate in visualizing metal, stone, and tooth particles of both sizes. However, CBCT was better for detecting glass particles in the periosteum. Although both imaging modalities visualized plastic particles poorly, CT was slightly better for detecting plastic particles, especially the smaller ones. Conclusion: Considering the lower patient radiation dose and cost, CBCT can be used with almost equal accuracy as CT for detecting foreign bodies of different compositions and sizes in multiple maxillofacial regions. However, CT performed better for detecting plastic particles.

• Imaging Science in Dentistry
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• v.52 no.1
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• pp.43-51
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• 2022

Purpose: The aim of this study was to evaluate the reliability of the Vectra M3 (3D Imaging System; Canfield Scientific, Parsippany, NJ, USA) in detecting chin asymmetry, and to assess whether the automatic markerless tracking function is reliable compared to manually plotting landmarks. Materials and Methods: Twenty subjects (18 females and 2 males) with a mean age of 42.5±10.5 years were included. Three-dimensional image acquisition was carried out on all subjects with simulated chin deviation in 4 stages (1-4 mm). The images were analyzed by 2 independent observers through manually plotting landmarks and by Vectra software auto-tracking mode. Repeated-measures analysis of variance and the Tukey post-hoc test were performed to evaluate the differences in mean measurements between the 2 operators and the software for measuring chin deviation in 4 stages. The intraclass correlation coefficient (ICC) was calculated to estimate the intra- and inter-examiner reliability. Results: No significant difference was found between the accuracy of manually plotting landmarks between observers 1 and 2 and the auto-tracking mode (P=0.783 and P=0.999, respectively). The mean difference in detecting the degree of deviation according to the stage was <0.5 mm for all landmarks. Conclusion: The auto-tracking mode could be considered as reliable as manually plotted landmarks in detecting small chin deviations with the Vectra^® M3. The effect on the soft tissue when constructing a known dental movement yielded a small overestimation of the soft tissue movement compared to the dental movement (mean value<0.5 mm), which can be considered clinically non-significant.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.323-331
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• 2021

Purpose: To investigate the diagnostic criteria of T1-weighted imaging (T1W) and time-of-flight (TOF) imaging for detecting intraplaque hemorrhage (IPH) of a vertebrobasilar artery (VBA) compared with simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) imaging. Materials and Methods: Eighty-seven patients with VBA atherosclerosis who underwent high resolution MR imaging for evaluation of VBA plaque were reviewed. The presence and location of VBA plaque and IPH on SNAP were determined. The signal intensity (SI) of the VBA plaque on T1W and TOF imaging was manually measured and the SI ratio against adjacent muscles was calculated. The receiver-operating characteristic (ROC) curve was used to compare the diagnostic accuracy for detecting VBA IPH. Results: Of 87 patients, 67 had IPH and 20 had no IPH on SNAP. The SI ratio between VBA IPH and temporalis muscle on T1W was significantly higher than that in the no-IPH group (235.9 ± 16.8 vs. 120.0 ± 5.1, P < 0.001). The SI ratio between IPH and temporalis muscle on TOF was also significantly higher than that in the no-IPH group (236.8 ± 13.3 vs. 112.8 ± 7.4, P < 0.001). Diagnostic efficacies of SI ratios on TOF and TIW were excellent (AUC: 0.976 on TOF and 0.964 on T1W; cutoff value: 136.7% for TOF imaging and 135.1% for T1W imaging). Conclusion: Compared with SNAP, cutoff levels of the SI ratio between VBA plaque and temporalis muscle on T1W and TOF imaging for detecting IPH were approximately 1.35 times.

• Journal of Gastric Cancer
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• v.13 no.3
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• pp.149-156
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• 2013

Purpose: Clinical stage of gastric cancer is currently assessed by computed tomography. Accurate clinical staging is important for the tailoring of therapy. This study evaluated the accuracy of clinical N staging using stomach protocol computed tomography. Materials and Methods: Between March 2004 and November 2012, 171 patients with gastric cancer underwent preoperative stomach protocol computed tomography (Jeju National University Hospital; Jeju, Korea). Their demographic and clinical characteristics were reviewed retrospectively. Two radiologists evaluated cN staging using axial and coronal computed tomography images, and cN stage was matched with pathologic results. The diagnostic accuracy of stomach protocol computed tomography for clinical N staging and clinical characteristics associated with diagnostic accuracy were evaluated. Results: The overall accuracy of stomach protocol computed tomography for cN staging was 63.2%. Computed tomography images of slice thickness 3.0 mm had a sensitivity of 60.0%; a specificity of 89.6%; an accuracy of 78.4%; and a positive predictive value of 78.0% in detecting lymph node metastases. Underestimation of cN stage was associated with larger tumor size (P<0.001), undifferentiated type (P=0.003), diffuse type (P=0.020), more advanced pathologic stage (P<0.001), and larger numbers of harvested and metastatic lymph nodes (P<0.001 each). Tumor differentiation was an independent factor affecting underestimation by computed tomography (P=0.045). Conclusions: Computed tomography with a size criterion of 8 mm is highly specific but relatively insensitive in detecting nodal metastases. Physicians should keep in mind that computed tomography may not be an appropriate tool to detect nodal metastases for choosing appropriate treatment.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• ETRI Journal
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• v.30 no.5
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• pp.750-752
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• 2008

This paper provides a novel method of detecting key captions containing player information in golf videos. We use the color pattern of captions and its repetition property to determine the key captions. The experimental results show that the proposed method achieves a much higher accuracy than existing methods.

• Journal of the Speleological Society of Korea
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• no.82
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• pp.17-25
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• 2007

The use of a low-frequency cave radio can also verify survey accuracy. A receiving unit on the surface can pinpoint the depth and location of a transmitter in a cave passage by measurement of the geometry of its radio waves. A survey over the surface from the receiver back to the cave entrance forms an artificial loop with the underground survey, whose loop-closure error can then be determined. In the past, caves were reluctant to redraw complex cave maps after detecting survey errors. Today, computer cartography can automatically redraw cave maps after data has been corrected.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1191-1200
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• 2006

A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.5-7
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• 1996

We propose a triangulation method based on stereo vision angles. We setup stereo vision systems which extract the depth information to a moving object by detecting a moving object using difference image method and obtaining the depth information by the triangulation method based on stereo vision angles. The feature point of a moving object is used the geometrical center of the moving object, and the proposed vision system has the accuracy of 0.2mm in the range of 400mm.