• Korean Journal of Radiology
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• v.22 no.3
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• pp.435-441
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• 2021

Objective: To evaluate the usefulness of the ventricular volume percentage quantified using three-dimensional (3D) brain computed tomography (CT) data for interpreting serial changes in hydrocephalus. Materials and Methods: Intracranial and ventricular volumes were quantified using the semiautomatic 3D threshold-based segmentation approach for 113 brain CT examinations (age at brain CT examination ≤ 18 years) in 38 patients with hydrocephalus. Changes in ventricular volume percentage were calculated using 75 serial brain CT pairs (time interval 173.6 ± 234.9 days) and compared with the conventional assessment of changes in hydrocephalus (increased, unchanged, or decreased). A cut-off value for the diagnosis of no change in hydrocephalus was calculated using receiver operating characteristic curve analysis. The reproducibility of the volumetric measurements was assessed using the intraclass correlation coefficient on a subset of 20 brain CT examinations. Results: Mean intracranial volume, ventricular volume, and ventricular volume percentage were 1284.6 ± 297.1 cm³, 249.0 ± 150.8 cm³, and 19.9 ± 12.8%, respectively. The volumetric measurements were highly reproducible (intraclass correlation coefficient = 1.0). Serial changes (0.8 ± 0.6%) in ventricular volume percentage in the unchanged group (n = 28) were significantly smaller than those in the increased and decreased groups (6.8 ± 4.3% and 5.6 ± 4.2%, respectively; p = 0.001 and p < 0.001, respectively; n = 11 and n = 36, respectively). The ventricular volume percentage was an excellent parameter for evaluating the degree of hydrocephalus (area under the receiver operating characteristic curve = 0.975; 95% confidence interval, 0.948-1.000; p < 0.001). With a cut-off value of 2.4%, the diagnosis of unchanged hydrocephalus could be made with 83.0% sensitivity and 100.0% specificity. Conclusion: The ventricular volume percentage quantified using 3D brain CT data is useful for interpreting serial changes in hydrocephalus.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.2
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• pp.31-39
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• 2016

Due to the temporal variation of inflow/outflow, the water tank is needed. For the calculation of water tank capacity, the absolute difference between cumulative amounts of supply(e.g., rainfall) and demand(e.g.,watering) is used. No matter the (-) and (+) the absolute maximum capacity of the subtraction is calculated as the capacity. In this paper, using rainfall and watering of greenhouse facilities, it is proved that the non-linear supply or demand can be applied, and it is proved also that the greater non-linear variation case. And as the time interval for monitoring is decreased, the basin or tank volume are increased, with approximately 10 days as the critical monitoring interval for the annual natural rainfall event.

• Journal of Korean Neurosurgical Society
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• v.60 no.4
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• pp.441-447
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• 2017

Objective : Computed tomography (CT)-based method of three dimensional (3D) analysis ($MIMICS^{(R)}$, Materialise, Leuven, Belgium) is reported as very useful software for evaluation of OPLL, but its reliability and reproducibility are obscure. This study was conducted to evaluate the accuracy of $MIMICS^{(R)}$ system, and inter- and intra-observer reliability in the measurement of OPLL. Methods : Three neurosurgeons independently analyzed the randomly selected 10 OPLL cases with medical image processing software ($MIMICS^{(R)}$) which create 3D model with Digital Imaging and Communication in Medicine (DICOM) data from CT images after brief explanation was given to examiners before the image construction steps. To assess the reliability of inter- and intra-examiner intraclass correlation coefficient (ICC), 3 examiners measured 4 parameters (volume, length, width, and length) in 10 cases 2 times with 1-week interval. Results : The inter-examiner ICCs among 3 examiners were 0.996 (95% confidence interval [CI], 0.987-0.999) for volume measurement, 0.973 (95% CI, 0.907-0.978) for thickness, 0.969 (95% CI, 0.895-0.993) for width, and 0.995 (95% CI, 0.983-0.999) for length. The intra-examiner ICCs were 0.994 (range, 0.991-0.996) for volume, 0.996 (range, 0.944-0.998) for length, 0.930 (range, 0.873-0.947) for width, and 0.987 (range, 0.985-0.995) for length. Conclusion : The medical image processing software ($MIMICS^{(R)}$) provided detailed quantification OPLL volume with minimal error of inter- and intra-observer reliability in the measurement of OPLL.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.143-147
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• 2007

This paper presents various interval estimation methods of binomial proportion for small n in multi-product small volume production and extremely small ^P like PPM or PPB fraction of defectives. This study classifies interval estimation of binomial proportion into three categories such as exact, approximate, Bayesian methods. These confidence intervals proposed in this paper can be applied to attribute process capability and attribute acceptance sampling plan for PPM or PPB.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.2
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• pp.19-36
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• 1991

The purpose of this paper is to calculate the excavation volume of unequal interval grid using nonlinear boundary in earthwork volume determination. The formulas by unmerical annlysis in this paper is compared with linear and nonlinear spot level method of unequal interval grid. As a result algorithm of derived formula by numerical analysis should provide a better accuracy than the linear and unlinear spot level method currently in use. Practical application of each method is illustrated by three model test.

• Journal of Biomedical Engineering Research
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• v.27 no.1
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• pp.6-13
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• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.

• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.1-9
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• 2001

We present a scheme and a data structure that decompose the space into adaptive-sized cells to improve the visualization of soft objects. Soft objects are visualized through the evaluation of the field functions at every point of the space. According to the propsed scheme, the affecting soft objects for a point in the space is searched through the data structure called interval tree based on the bounding volume of the components, which represent a soft object whose defining primitive(skeleton) is a simple geometric object such as point or line segment. The bounding volume of each component is generated with respect to the radius of a local field function of the component, threshold value, and the relations between the components and other neighboring components. The proposed scheme can be used in many applications for soft objects such as modeling and rendering, especially in interactive modeling process.

• Korean Journal of Radiology
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• v.24 no.9
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• pp.849-859
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• 2023

Objective: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. Materials and Methods: We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. Results: Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the non-sarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the non-myosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25-2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84-3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08-3.54]; P = 0.027). Conclusion: Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.465-475
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• 2001

Recent1y, there is growing attention on the researches of inducing association rules from large volume of database. One of them is the method that can be applied to quantitative attribute data. This paper presents a new method for generating large-interval itemsets, which uses locality for partitioning the range of data. This method can minimize the loss of data-inherent characteristics by generating denser large-interval items than other methods. Performance evaluation results show that our new approach is more efficient than previously proposed techniques.

• Clinics in Shoulder and Elbow
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• v.21 no.3
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• pp.134-137
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• 2018

Background: In a previous study undertaken to quantify capsular volume in rotator cuff interval or axillary pouch, significant differences were found between controls and patients with instability. However, the results obtained were derived from two-dimensional cross sectional areas. In our study, we sought correlation between three-dimensional (3D) capsular volumes, as measured by magnetic resonance arthrography (MRA), and multidirectional instability (MDI) of the shoulder. Methods: The MRAs of 21 patients with MDI of the shoulder and 16 control cases with no instability were retrospectively reviewed. Capsular areas determined by MRA were translated into 3D volumes using 3D software Mimics ver. 16 (Materilise, Leuven, Belgium), and glenoid surface area was measured in axial and coronal MRA views. Then, the ratio between capsular volume and glenoid surface area was calculated, and evaluated with control group. Results: The ratio between 3D capsular volume and glenoid surface area was significantly increased in the MDI group ($3.59{\pm}0.83cm^3/cm^2$) compared to the control group ($2.53{\pm}0.62cm^3/cm^2$) (p<0.01). Conclusions: From these results, we could support that capsular volume enlargement play an important role in MDI of the shoulder using volume measurement.