• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.110-119
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• 2010

In this paper, we propose an automatic segmentation of the prostate using intensity distribution and gradient information in MR images. First, active shape model using adaptive intensity profile and multi-resolution technique is used to extract the prostate surface. Second, hole elimination using geometric information is performed to prevent the hole from occurring by converging the surface shape to the local optima. Third, the surface shape with large anatomical variation is corrected by using 2D gradient information. In this case, the corrected surface shape is often represented as rugged shape which is generated by the limited number of vertices. Thus, it is reconstructed by using surface modelling and smoothing. To evaluate our method, we performed the visual inspection, accuracy measures and processing time. For accuracy evaluation, the average distance difference and the overlapping volume ratio between automatic segmentation and manual segmentation by two radiologists are calculated. Experimental results show that the average distance difference was 0.3${\pm}$0.21mm and the overlapping volume ratio was 96.31${\pm}$2.71%. The total processing time of twenty patient data was 16 seconds on average.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.846-855
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• 2007

Significant feature extraction in cancer cell image analysis is an important process for grading cell carcinoma. In this study, we propose a method for 3D quantitative analysis of cell nuclei based upon digital image cytometry. First, we acquired volumetric renal cell carcinoma data for each grade using confocal laser scanning microscopy and segmented cell nuclei employing color features based upon a supervised teaming scheme. For 3D visualization, we used a contour-based method for surface rendering and a 3D texture mapping method for volume rendering. We then defined and extracted the 3D morphological features of cell nuclei. To evaluate what quantitative features of 3D analysis could contribute to diagnostic information, we analyzed the statistical significance of the extracted 3D features in each grade using an analysis of variance (ANOVA). Finally, we compared the 2D with the 3D features of cell nuclei and analyzed the correlations between them. We found statistically significant correlations between nuclear grade and 3D morphological features. The proposed method has potential for use as fundamental research in developing a new nuclear grading system for accurate diagnosis and prediction of prognosis.

• Journal of radiological science and technology
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• v.40 no.1
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• pp.121-126
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• 2017

A technique for producing the ear shell for a hearing aid using DICOM (Digital Imaging and Communication in Medicine) image and a 3D printing was studied. It is a new application method, and is an application technique that can improve the safety and infection of hearing aid users and can reduce the production time and process stages. In this study, the effects on the shape surface were examined before and after the printing of the ear shell using a 3D printer based on the values obtained from the raw data of the DICOM images at the volumes of 0.5 mm, 1.0 mm, and 2.0 mm, respectively. Before the printing, relative relationship was compared with respect to the STL (STereoLithography) file structure; and after the printing, the intervals of the layered structure of the ear shell shape surface were compared by magnifying them using a microscope. For the STL file structure, the numbers of triangular vertices, more than five intersecting points, and maximum intersecting points were large in the order of 0.5 mm, 1.0 mm, and 2.0 mm, respectively; and the triangular structure was densely distributed in the order of the bending, angle, and crest regions depending on the sinuosity of the external auditory meatus shape. As for the ear shell shape surface examined by the digital microscope, the interval of the layered structure was thick in the order of 2.0 mm, 1.0 mm, and 0.5 mm. For the STL surface structure mentioned above, the intersecting STL triangular structure was denser as the sinuosity of the 3D ear shell shape became more irregular and the volume of the raw data decreased.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.326-334
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• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.311-318
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• 2014

This paper is to introduce a lighting source controller using high brightness LED to create a clear and reliable condition for an accurate measurement and testing, which is a core technology in clinical image system and mechanical automation system. This controller is designed to supply a stable power in a constant-current system by installing a high brightness LED driver, and to improve the reproducibility of brightness by using 32-bit ARM processor core, dividing brightness quantity into 256 levels, making the remote control and the external interface possible, and preventing and digitizing the brightness inaccuracy caused by errors of resistance values. This controller enables the lighting range to be wide and possible in a low lighting level compared to analog, adds the RS-485 communication function, and makes it for the users to control the on-off function and the dimming level by receiving date from an external device.

• Convergence Security Journal
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• v.8 no.3
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• pp.41-49
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• 2008

Other server based-application and the need of more complex interaction is required with functional strengthening and variational uses of mobile device. And mobile environments make a problem of continuous of web-service by making a problem of instance cutting between web-server and mobile device which acts as a client because of mobility. Therefore, this paper embodies a framework which keeps security and connectivity between HTTP based web-service and mobile device, and is for connection to web-service of mobile device which uses WAP in a standard protocol based mobile environment of mobile web-service for continuous web-service. This paper is analyzed in the same standard condition to compared functional delay which is based on HTTP and WAP access, and data transmission volume. Also it investigates improvement of execution overhead which is brought by interaction process.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.2
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• pp.37-44
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• 2020

In this paper, we proposed that a fully automatic multi-class whole heart segmentation algorithm using deep learning. The proposed method is based on U-Net architecture which consist of recurrent convolutional block, residual multi-dilated convolutional block. The evaluation was accomplished by comparing automated analysis results of the test dataset to the manual assessment. We obtained the average DSC of 96.88%, precision of 95.60%, and recall of 97.00% with CT images. We were able to observe and analyze after visualizing segmented images using three-dimensional volume rendering method. Our experiment results show that proposed method effectively performed to segment in various heart structures. We expected that our method can help doctors and radiologist to make image reading and clinical decision.

• Progress in Medical Physics
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• v.17 no.3
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• pp.167-172
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• 2006

Catheter fragment and embolism are both potentially serious complications associated with the use of an intravenous (IV) catheter for contrast media bolus injection, and may be followed by serious or lethal sequelae. Though catheter fragment is a rare complication of IV catheter insertion, especially in peripheral veins, CT can be used to detect residual fragment. This study demonstrates the utility of MDCT to localize a small, subtle peripheral venous catheter, which can be easily reformatted of MDCT reformations. Various 3D techniques such as MPR and MIP, volume rendering, and shaded-surface displays are currently available for reconstructing MDCT data. Advances in MDCT technology contribute substantially to the detection and accurate localization of smaller IV catheter fragment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2747-2754
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• 2012

This thesis explains the development of multiple LCD system with the additional function to maximize the utilization of PC contents. The newly developed system is composed of host LCD and slave LCD. Host LCD decodes and outputs the image and voice of NTSC, PAL, SECAM signals. It also converts the decoded signals into LVDS signals before transmitting them to slave LCD stage. In addition, the installation of CF Memory and USB Memory helps display multi-media data. Unlike the host LCD, since not including the tuner and memory part, the slave LCD can't receive TV signals and play video signals. It only has the function to receive LVDS image signals and display on a LCD panel. This newly developed multi-LCD system has competitiveness in various aspects. With its simple structure, the failure rate, price and display power are relatively low due to its simplification of the control part. It has price and functional competitiveness as the product whose host LCD can control the entire slave LCD in terms of channel, volume, and video output.