• Journal of Chest Surgery
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• v.53 no.5
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• pp.301-305
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• 2020

Background: Radiographic modalities have been commonly used to evaluate pectus carinatum (PC), and compressive orthotic bracing is the most widely accepted treatment method. The aim of this study was to determine the efficacy of 3-dimensional (3D) body surface scanning as an alternative modality for the evaluation of PC. Methods: The medical records of 63 patients with PC who were treated with compressive orthotic bracing therapy between July 2017 and February 2019 were retrospectively analyzed. Using both 2-view chest radiography (posteroanterior and lateral view) and 3D body scanning, the height of maximal protrusion of the chest wall was measured both before and after 2 weeks of bracing therapy. The difference between the pre- and post-treatment measurements was calculated for both modalities, and these differences were compared and analyzed. Results: Based on the comparison between the pre- and post-treatment radiographs, bracing therapy produced favorable outcomes in all patients (p<0.001). The measurements obtained via 3D scanning were strongly correlated with those obtained via chest radiography (r=0.60). Conclusion: Based on the findings of this study, 3D body surface scanning appears to be an effective, radiation-free, and simple method for the post-treatment follow-up evaluation of PC, and thus can be considered an alternative to radiography.

• Investigative Magnetic Resonance Imaging
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• v.5 no.1
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• pp.57-65
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• 2001

Purpose : $T_2$-weighted half courier Echo Planar Imaging (T2HEPI) method is proposed to reduce measurement time of existing EPI by a factor of 2. In addition, high $T_2$ contrast is obtained for clinical applications. High resolution single-shot EPI images with $T_2$ contrast are obtained with $128{\times}128$ matrix size by the proposed method. Materials and methods : In order to reduce measurement time in EPI, half courier space is measured, and rest of half courier data is obtained by conjugate symmetric filling. Thus high resolution single shot EPI image with $128{\times}128$ matrix size is obtained with 64 echoes. By the arrangement of phase encoding gradients, high $T_2$ weighted images are obtained. The acquired data in k-space are shifted if there exists residual gradient field due to eddy current along phase encoding gradient, which results in a serious problem in the reconstructed image. The residual field is estimated by the correlation coefficient between the echo signal for dc and the corresponding reference data acquired during the pre-scan. Once the residual gradient field is properly estimated, it can be removed by the adjustment of initial phase encoding gradient field between $70^{\circ}$ and $180^{\circ}$ rf pulses. Results : The suggested T2EPl is implemented in a 1.0 Tela whole body MRI system. Experiments are done with the effective echo times of 72ms and 96ms with single shot acquisitions. High resolution($128{\times}128$) volunteer head images with high $T_2$ contrast are obtained in a single scan by the proposed method. Conclusion : Using the half courier technique, higher resolution EPI images are obtained with matrix size of $128{\times}128$ in a single scan. Furthermore $T_2$ contrast is controlled by the effective echo time. Since the suggested method can be implemented by software alone (pulse sequence and corresponding tuning and reconstruction algorithms) without addition of special hardware, it can be widely used in existing MRI systems.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.411-417
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• 2015

To distinguish between HCC and HH is one of the important test methods in determining the treatment method by determining the treatment method by distinguishing malignant growth and benign tumors in liver CT scan. Currently, the specialist is reading CT images by their subjective judgment. So, the purpose of this study is to treat reading the CT images even more objective way. The test times after injection contrast medium in this study are the before injection phase(Pre.), artery phase(35sec), portal phase(70sec) and delay phase(180sec). The general pattern change of HCC in change of contrast enhancement pattern shows 26.6% matching. And the case of HH shows 16.6% matching. In order to observe the change of HU value between HCC and HH, each average values and standard deviation was confirm and as a result, it shows the lagre difference between artery and portal phase in lesion.(HCC$19.76{\pm}23.52$, HH$60.23{\pm}29.43$). And it shows the 76.6% matching in HCC and 80.0% matching in HH. Thorough this study, to suggest a HU value as objective analysis method and if the anlaysis method was used in clinical will assist in the diagnosis.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.500-509
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• 2001

Image compression based on Wavelet gives much better quality than JPEG based on DCT, but suffers from ringing or blurring effects around edges as the compression is increased. In this paper, we proposed enhanced image compression by pre-processing wavelet coefficients. This pre-processing is performed by making a low threshold and enhanced by zerotree scan method when subband's zerotrees are established. It might increase significants coefficient by means of modifying the threshold and reflect on the orientation of subbands. Some experimental results show our method is more efficient than the conventional methods, JPEG. And then the developed coding scheme improves the quality of images and visually shows more pleasing results for most practical images.

• Architectural research
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• v.21 no.4
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• pp.111-116
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• 2019

The premise of this research is the recent advancement of Building Information Modeling(BIM) Technology and Laser Scanning Technology(3D Scanning). The purpose of the paper is to amplify the potential offered by the combination of BIM and Point Cloud Data (PCD) for structural analysis. Today, enormous amounts of construction site data can be potentially categorized and quantified through BIM software. One of the extraordinary strengths of BIM software comes from its collaborative feature, which can combine different sources of data and knowledge. There are vastly different ways to obtain multiple construction site data, and 3D scanning is one of the effective ways to collect close-to-reality construction site data. The objective of this paper is to emphasize the prospects of pre-scanning and post-scanning automation algorithms. The research aims to stimulate the recent development of 3D scanning and BIM technology to develop Scan-to-BIM. The paper will review the current issues of Scan-to-BIM tasks to achieve As-Built BIM and suggest how it can be improved. This paper will propose a method of coordinating and utilizing PCD for construction and structural analysis during construction.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.41-46
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• 2011

Purpose: The result of exam using an imaging device is very closely related with the image quality. Moreover, this image quality can be changed according to the condition of image acquisition and evaluation method. In this study, we evaluated the image quality according to the difference of pre-set method in PET/CT image. Materials & Methods: PET/CT Discovery STe16 (GE Healthcare, Milwaukee, USA), Chest PET phantom (Experiment 1) and 94 NEMA phantom (Experiment 2) were used. Phantom were filled with $^{18}F$-FDG maintaining hot sphere and background ratio to 4:1. In the case of experiment 1, we set the radio activity concentration on 3.5, 6.0, 8.6 kBq/mL. In the case of experiment 2, we set the radio activity concentration on 3.3, 5.5, 7.7, 9.9, 12.1, 16.5 kBq/mL. All experiments were performed with the time-set method for 2 minutes 30 seconds per frame and the count-set method with one hundred million counts in 3D mode after CT transmission scan. For the evaluation of the image quality, we compared each results by using the NECR and SNR. Results: In the experiment 1, both the NECR and SNR were increased as radioactivity concentration getting increased. The NECR was shown as 53.7, 66.9, 91.4. and SNR was shown as 7.9, 10.0, 11.7. Both the NECR and SNR were increased in time-set method. But the count-set method's pattern was not similar with the time-set method. The NECR was shown as 53.8, 69.1, 97.8, and SNR was shown as 14.1, 14.7 14.4. The SNR was not increased in count-set method. In experiment 2, results of both the NECR and SNR were shown as 45.1, 70.6, 95.3, 115.6, 134.6, 162.2 and 7.1, 8.8, 10.6, 11.5, 12.7, 14.0. These results were shown similar patten with the experiment 1. Moreover, when the count-set method was applied, the NECR was shown as 42.1, 67.3, 92.1, 112.2, 130.7, 158.7, and SNR was shown as 15.2, 15.9, 15.6, 15.4, 15.5, 14.9. The NECR was increased but SNR was not shown same pattern. Conclusion: Increment of administered radioactivity improves the quality of image unconcerned with the pre-set method. However, NECR was not influenced by increment of total acquisition counts through simple increasing scan duration without increment of administered activity. In case of count-set method, the SNR was shown similar value despite of increment of radioactivity. So, the administered activity is more important than the scan duration. And we have to consider that evaluation of image quality using only SNR may not be appropriate.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.102.3-102
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• 2001

In this paper, we propose a novel method that can detect face region effectively with fuzzy theory and neural network We make fuzzy rules and membership functions to describe the face color. In this algorithm, we use a perceptually uniform color space to increase the accuracy and stableness of the nonlinear color information. We use this model to extract the face candidate, and then scan it with the pre-built sliding window by using a neural network-based pattern-matching method to find eye. A neural network examines small windows of face candidate, and decides whether each window contains eye. We can standardize the face candidate geometrically with detected eyes.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.434-440
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• 2022

Liver transplantation is a critical used treatment method for patients with end-stage liver disease. The number of cases of living donor liver transplantation is increasing due to the imbalance in needs and supplies for brain-dead organ donation. As a result, the importance of the accuracy of the donor's suitability evaluation is also increasing rapidly. To measure the donor's liver volume accurately is the most important, that is absolutely necessary for the recipient's postoperative progress and the donor's safety. Therefore, we propose liver segmentation in abdominal CT images from pre-operation, POD 7, and POD 63 with a two-dimensional U-Net. In addition, we introduce an algorithm to measure the volume of the segmented liver and measure the hepatectomy rate and regeneration rate of pre-operation, POD 7, and POD 63. The performance for the learning model shows the best results in the images from pre-operation. Each dataset from pre-operation, POD 7, and POD 63 has the DSC of 94.55 ± 9.24%, 88.40 ± 18.01%, and 90.64 ± 14.35%. The mean of the measured liver volumes by trained model are 1423.44 ± 270.17 ml in pre-operation, 842.99 ± 190.95 ml in POD 7, and 1048.32 ± 201.02 ml in POD 63. The donor's hepatectomy rate is an average of 39.68 ± 13.06%, and the regeneration rate in POD 63 is an average of 14.78 ± 14.07%.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.154-160
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• 2023

Recently, with the activation of eBook services, books are being published simultaneously as physical books and digitized eBooks. Paper books are more expensive than e-books due to printing and distribution costs, so demand for relatively inexpensive e-books is increasing. There are cases where previously published physical books cannot be digitized due to the circumstances of the publisher or author, so there is a movement among individual users to digitize books that have been published for a long time. However, existing research has only studied the advancement of the pre-processing process that can improve text recognition before applying OCR technology, and there are limitations to digitization depending on the condition of the book. Therefore, support for book digitization services depending on the condition of the physical book is needed. need. In this paper, we propose a method to support digitalization services according to the status of physical books held by book owners. Create images by scanning books and extract text information from the images through OCR. We propose a method to recover text that cannot be extracted depending on the state of the book using BERT, a natural language processing deep learning model. As a result, it was confirmed that the recovery method using BERT is superior when compared to RNN, which is widely used in recommendation technology.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.