• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.21-32
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• 1999

Purpose: To evaluate the effect of variable scanning protocols of computed tomography for evaluation of pre-implant site of the mandible through the comparison of the reformatted cross-sectional images of helical CT scans obtained with various imaging parameters versus those of conventional CT scans. Materials and Methods: A dry mandible was imaged using conventional nonoverlapped CT scans with 1 mm slice thickness and helical CT scans with 1 mm slice thickness and pitches of 1.0, 1.5. 2.0, 2.5 and 3.0. All helical images were reconstructed at reconstruction interval of 1 mm. DentaScan reformatted images were obtained to allow standardized visualization of cross-sectional images of the mandible. The reformatted images were reviewed and measured separately by 4 dental radiologists. The image qualities of continuity of cortical outline. trabecular bone structure and visibility of the mandibular canal were evaluated and the distance between anatomic structures were measured by 4 dental radiologists. Results: On image qualities of continuity of cortical outline. trabecular bone structure and visibility of the mandibular canal and in horizontal measurement. there was no statistically significant difference among conventional and helical scans with pitches of 1.0. 1.5 and 2.0. In vertical measurement. there was no statistically significant difference among the conventional and all imaging parameters of helical CT scans with pitches of 1.0, 1.5, 2.0, 2.5 and 3.0. Conclusion: The images of helical CT scans with 1 mm slice thickness and pitches of 1.0, 1.5 and 2.0 are as good as those of conventional CT scans with 1 mm slice thickness for evaluation of predental implant site of the mandible. Considering the radiation dose and patient comfort, helical CT scans with 1 mm slice thickness and pitch of 2.0 is recommended for evaluation of pre-implant site of the mandible.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.889-895
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• 2010

This study compared the effects of craniocervical flexion exercise with conservative cervical flexion exercise in workers with chronic neck pain. Subjects were randomly allocated to two groups: control (n=20) and experimental group (n=20), respectively. The conservative exercise for the control group consisted of cervical flexion exercise, whereas the experimental group performed a craniocervical flexion exercise. To compare the two groups, the visual analogue scale (VAS) for a pain, neck disability index (NDI) for a neck disability scale, and cross sectional area (CSA) of longus colli muscle using ultrasound image were assessed on pre-intervention, post-intervention, and 2 weeks follow-up. 2-way repeated ANOVA was used with Bonferroni post-hoc test. (1) There were significant main effects (within and between groups) (p<0.05) and interaction effect (p<0.05) in VAS. Post-hoc test revealed that there were significant differences in all pair-wise comparisons. (2) There were significant main effects (within and between groups) (p<0.05) and interaction effect (p<0.05) in NDI. Post-hoc test revealed that there were significant differences between pre-intervention and post-intervention, pre-intervention and 2 weeks follow-up. (3) There were significant main effects (within and between groups) (p<0.05) and interaction effect (p<0.05) in CSA of longus colli muscle. Post-hoc test revealed that there were significant differences in all pair-wise comparisons. The findings indicate that craniocervical flexion exercise are more effective for improving pain, neck disability, and CSA of longus colli muscle than cervical flexion exercise in workers with chronic neck pain.

• Women's Health Nursing
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• v.30 no.3
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• pp.238-249
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• 2024

Purpose: This study investigated the prevalence of postpartum depression (PPD) and explored associated factors among mothers attending postnatal care in Bhutan. Methods: A cross-sectional study was conducted from August to November 2023 at a national referral hospital in Thimphu, the capital city of Bhutan. In total, 314 mothers were recruited. Sociodemographic, psychosocial, obstetric, and infant-related data were collected using questionnaires. The Edinburgh Postnatal Depression Scale, with a threshold of ≥11, was employed to screen for PPD, and logistic regression was used to test the potential factors. Results: The prevalence of PPD was 14.97%. Mothers with a perceived change in body image (adjusted odds ratio [AOR], 4.40; 95% confidence interval [CI], 1.91-10.17; p=.001), perceived heightened stress after delivery (AOR, 3.74; 95% CI, 1.45-9.67; p=.006), poor relationship with inlaws (AOR, 2.57; 95% CI, 1.24-5.30; p=. 011), and negative birth experience (AOR, 2.42; 95% CI, 1.17-5.00; p=.016) demonstrated significantly higher odds of developing PPD. However, mothers with a higher monthly family income (Bhutanese ngultrum [Nu.] 20,000 to <50,000; AOR, 0.35; 95% CI, 0.13-0.92; p=.033), ≥Nu. 50,000 (AOR, 0.37; 95% CI, 0.13-1.07, p=.067) compared to <Nu. 20,000, and advanced gestational age (37 to <41 weeks; AOR, 0.25; 95% CI, 0.09-0.71; p=.009) and ≥41 weeks (AOR, 0.08; 95% CI, 0.00-0.75; p=.028) compared to <37 weeks had significantly lower risks of PPD. Conclusion: To mitigate the prevalence and risk of PPD, prioritizing screening strategies and interventions may benefit mothers with perceived changes in body image and heightened perceived stress after delivery, poor relationships with in-laws, and those with negative birth experiences.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.247-257
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• 2003

This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

• Computers and Concrete
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• v.33 no.5
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• pp.481-496
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• 2024

Internal erosion around pipes can lead to the failure of earth dams through various mechanisms. This study investigates the displacement patterns in earth dam models under three different failure modes due to internal erosion, using digital image correlation (DIC) methods. Three failure modes—erosion along a pipe (FM1), pipe leakage leading to soil erosion (FM2), and erosion in a pipe due to defects (FM3)—are analyzed using two- and three-dimensional image- processing techniques. The internal displacement of the cross-sectional area and the surface displacement of the downstream slope in the dam models are monitored using an image acquisition system. Physical model tests reveal that FM1 exhibits significant displacement on the upper surface of the downstream slope, FM2 shows focused displacement around the pipe defect, and FM3 demonstrates increased displacement on the upstream slope. The variations in internal and surface displacements with time depend on the segmented area and failure mode. Analyzing the relationships between internal and surface displacements using Pearson correlation coefficients reveals various displacement patterns for the segmented areas and failure modes. Therefore, the image-based characterization methods presented in this study may be useful for analyzing the displacement distribution and behavior of earth dams around pipes, and further, for understanding and predicting their failure mechanisms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.8
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• pp.658-666
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• 1989

In this paper, an efficient algorithm for estimation volume and surface area and a reconstruction algorithm for 3-dimensional graphics are presented.In order to improve computing efficiency, the graph theory is utilized and the algorithm to obtain proper contour points is developed by considering several tolerances. Search for the contour points is limited by the change of curvature of cross sectional contour to provide efficiency in searching the minimum cost path. In computer simulation of these algorithms, the results show that, for the tolerance values of 1.001 and 1.002, the execution time reduced to 66%-80% and the error for the measured value is less than 3%. The reconstructed 3-dimensional images from the cross sections can be analyzed in many directions using the graphic scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.347-365
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• 2013

The performance of finger-vein recognition methods is limited by camera optical defocusing, the light-scattering effect of skin, and individual variations in the skin depth, density, and thickness of vascular patterns. Consequently, all of these factors may affect the image quality, but few studies have conducted quality assessments of finger-vein images. Therefore, we developed a new finger-vein recognition method based on image quality assessment. This research is novel compared with previous methods in four respects. First, the vertical cross-sectional profiles are extracted to detect the approximate positions of vein regions in a given finger-vein image. Second, the accurate positions of the vein regions are detected by checking the depth of the vein's profile using various depth thresholds. Third, the quality of the finger-vein image is measured by using the number of detected vein points in relation to the depth thresholds, which allows individual variations of vein density to be considered for quality assessment. Fourth, by assessing the quality of input finger-vein images, inferior-quality images are not used for recognition, thereby enhancing the accuracy of finger-vein recognition. Experiments confirmed that the performance of finger-vein recognition systems that incorporated the proposed quality assessment method was superior to that of previous methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.9
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• pp.140-147
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• 2007

As the use of robots in surgeries becomes more frequent, the registration of medical devices based on images becomes more important. This paper presents two numerical algorithms for the registration of cross-sectional medical images such as CT (Computerized Tomography) or MRI (Magnetic Resonance Imaging) by using the geometrical information from helix or line fiducials. Both registration algorithms are designed to be used for a surgical robot that works inside a cavity of human body. This paper also reports details about the fiducial pattern that includes four helices and one line. The algorithms and the fiducial pattern were tested in various computer-simulated situations, and the results showed excellent overall registration accuracy.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.714-719
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• 2004

This paper presents two numerical algorithms for registration of cross-sectional medical images such as CT (Computerized Tomography) or MRI (Magnetic Resonance Imaging) by using geometrical information from helix or line fiducials. The registration algorithms are designed to be used for a surgical robot working inside cavities of human body. A cylindrical device with a combination of line and helix fiducials were also devised and is supposed to be attached to the end-effector of surgical robot. The algorithms and the fiducial pattern were tested in various computer-simulated situations, and the results indicate excellent overall registration accuracy.