• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.5
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• pp.20-27
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• 2001

The purpose of this study is to investigate and compare the validity and the reliability of the visual simulation method using the internet. For this. the evaluation of the artificial and natural landscape through the medium of color slides are compared with the internet survey. Data is analysed through the comparison of t-test between the two media by landscape type, and spatial image is analysed by factor analysis algorithm. Principle component analysis using Varimax Method is applied for extraction and factor rotation respectively. The results of this study can be summarized as follows; There are no statistical differences between the two methods with artificial and natural landscape in the total data that included second tests. Factors covering the spatial image are found to be \`aesthetic\`, \`spatial shape\`, and \`familiarity\`. Total variance is obtained as 66.4%. There are no statistical differences between the two methods in 2/3 of the cases. In the case of far view of artificial landscape, the results of the t-test show that the two methods are exactly the same. Especially in the case of the artificial far landscape shows no difference of all factors between two methods. There are no differences between first and second tests of the same media and the same landscape type. And it shows the reliability of this method. These results suggest that the probability that the internet can be used as a medium of landscape evaluation and gathering information on anyone\`s landscape image. Simulation techniques with the internet survey method should be further developed for practical application.

• Medical Lasers
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• v.10 no.3
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• pp.123-131
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• 2021

Optical imaging modalities with properties of real-time, non-invasive, in vivo, and high resolution for image-guided surgery have been widely studied. In this review, we introduce two optical imaging systems, that could be the core of image-guided surgery and introduce the system configuration, implementation, and operation methods. First, we introduce the optical coherence tomography (OCT) system implemented by our research group. This system is implemented based on a swept-source, and the system has an axial resolution of 11 ㎛ and a lateral resolution of 22 ㎛. Second, we introduce a fluorescence imaging system. The fluorescence imaging system was implemented based on the absorption and fluorescence wavelength of indocyanine green (ICG), with a light-emitting diode (LED) light source. To confirm the performance of the two imaging systems, human malignant melanoma cells were injected into BALB/c nude mice to create a xenograft model and using this, OCT images of cancer and pathological slide images were compared. In addition, in a mouse model, an intravenous injection of indocyanine green was used with a fluorescence imaging system to detect real-time images moving along blood vessels and to detect sentinel lymph nodes, which could be very important for cancer staging. Finally, polarization-sensitive OCT to find the boundaries of cancer in real-time and real-time image-guided surgery using a developed contrast agent and fluorescence imaging system were introduced.

• Journal of the Korean Society of Costume
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• v.53 no.4
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• pp.1-16
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• 2003

The purpose of this study is to investigate the sensibility images of Korean Traditional Chumoni. The detailed methodology of this study is as follows. Selections of stimuli to analyse the sensibility images of Korean Traditional Chumoni were made up of 15 stimuli. The survey has been done for the 15 slide stimuli with semantic differential hi-polar scales which are consist of 23 couples of sensibility words. The subjects were 150 female students majoring in clothing and textile. 150 male students majoring in other department and 150 female students majoring in other department in the twenties between 2001. 3. 30 and 2001. 4. 4. The obtained data were analyzed by factor analysis, cluster analysis. ANOVA. The major finds were as follows. 1. To explain the hierarchy of the sensibility of Korean Traditional Chumoni, two image groups were classified, one is noble and characteristic image the other is splendid and intensive image. Finally it represented noble and splendid image. 2. As result of the factor analysis. 3 factors which are Attraction, Decorativeness, Gravity were found to be constructing factors for the sensibility images of Korean Traditional Chumoni. 3. By cluster analysis, 4 clusters were determined according to Korean Traditional Chumoni. Cluster 1 is splendid. multi-colored and realistic in patteren. Cluster 2 is consist of 'true chumonis' and one-colored. Cluster 3 is modal in pattern. Cluster 4 is simple without any decorations. As to the difference of image of Korean Traditional Chumoni, there were significant differences amang 3 factors by cluster Cluster 1 was found most attractive and grave. Cluster 2 was found most decorative. 4. As to the difference of image of Korean Traditional Chumoni, there were significant differences amang 3 factors by decoration. Gold foil was found most attractive and grave. Embroidery was found most decorative. 5. As to the difference of image of Korean traditional chumoni, there were differences in Decorativeness and Gravity by sex and there were differences in Attraction by major.

• Journal of Biosystems Engineering
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• v.35 no.4
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• pp.257-261
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• 2010

Surface energy is the principal factor of anti-condensation. High surface energy appears hydrophilic itself and low surface energy represents hydrophobic itself. The contact angle is widely being used for measurement of surface energy of materials, evaluation of coating performances, measurement of wettability, and so on. However, the existing contact angle measuring system is so expensive for purchasing and complicated, so it takes a lot of time and money to use. This study was conducted to develop the algorithm for evaluating hydrophilic performance through measuring the contact angle of water droplet automatically, and fabricate relatively simple measuring system using a low-cost monochrome camera and image processing. A constant amount of water was firstly allocated on a slide by a micropipette, and then the image of water droplet was captured by monochrome digital camera and sent to a computer. The image was binarized and then reduced noises by labeling. Finally, the contact angle of water droplet was computed by using three points (left, right, and top coordinates), simple linear mathematics, and trigonometric function. The experimental results demonstrated the accuracy and reproducibility of the developed system showing less deviations and deviation ratio.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.161-173
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• 1999

This study was performed to compare the bone mineral densities measured at mandibular premolar area by copper-equivalent image and hydroxyapatite phantom with those measured at radius by dual energy absorptiometry and to evaluate the clinical usefulness of Digital system with slide scanner, copper-equivalent image, and hydroxyapatite phantom. For experiment. intraoral radiograms of 15 normal subjects ranged from 20 years old to 67 old were taken with copper-step wedge at mandibular premolar area and bone mineral densities calculated by conversion equation to bone mineral density of hydroxyapatite were compared with those measured at radius distal 1/3 area by Hologic QDR-1000. Obtained results as follows: 1) The conversion equation was Y=5.97X-0.25 and its determination coefficient was 0.9967. The coefficient of variation in the measurement of copper-equivalent value ranged from 4％ to 8％ and showed high reproducibility. 2) The coefficient of variation in the measurement of bone mineral density by the equation ranged from 7％ to 8％ and showed high reproducibility. 3) The bone mineral densities ranged from 0.35 to 0.79g/cm2 at mandibular premolararea. 4) The correlation coefficient between bone mineral densities at mandibular premolar area and those at radius distal 1/3 area was 0.8965. As summary, digital image analyzing system using copper-equivalent image and hydroxyapatite phantom appeared to be clinically useful to measure the bone mineral density at dental area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.232-239
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• 2003

This paper discusses the design and implementation of a human-oriented interface based on computer vision that efficiently controls presentation slides. The user does not have to be confined to a keyboard or mouse any more, and can move around more freely because slides for presentation can be up and down using a general laser pointer that is used for presentation. Regions for virtual buttons are set on the slide so that the user can conveniently point the buttons using the laser pointer. We have proposed a simple and efficient method that computes the button areas in the image without complicated calibration. The proposed method has been implemented based on Microsoft PowerPoint ; moreover it can be applied to other PowerPoint-like presentation softwares. Our method for human-centered slide control enables the user to give audiences a more interactive presentation in a natural way.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.127-135
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• 2023

Accurate segmentation of histopathology whole slide images (WSIs) is a crucial task for disease diagnosis and treatment planning. However, conventional automated segmentation algorithms may not always be applicable to WSI segmentation due to their large size and variations in tissue appearance, staining, and imaging conditions. Recent advances in interactive segmentation, which combines human expertise with algorithms, have shown promise to improve efficiency and accuracy in WSI segmentation but also presented us with challenging issues. In this paper, we propose a novel interactive segmentation method, ZoomISEG, that leverages multi-resolution WSIs. We demonstrate the efficacy and performance of the proposed method via comparison with conventional single-scale methods and an ablation study. The results confirm that the proposed method can reduce human interaction while achieving accuracy comparable to that of the brute-force approach using the highest-resolution data.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.72-78
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• 2019

Pathology is the motor that drives healthcare to understand diseases. The way pathologists diagnose diseases, which involves manual observation of images under a microscope has been used for the last 150 years, it's time to change. This paper is specifically based on tumor detection using deep learning techniques. Pathologist examine the specimen slides from the specific portion of body (e-g liver, breast, prostate region) and then examine it under the microscope to identify the effected cells among all the normal cells. This process is time consuming and not sufficiently accurate. So, there is a need of a system that can detect tumor automatically in less time. Solution to this problem is computational pathology: an approach to examine tissue data obtained through whole slide imaging using modern image analysis algorithms and to analyze clinically relevant information from these data. Artificial Intelligence models like machine learning and deep learning are used at the molecular levels to generate diagnostic inferences and predictions; and presents this clinically actionable knowledge to pathologist through dynamic and integrated reports. Which enables physicians, laboratory personnel, and other health care system to make the best possible medical decisions. I will discuss the techniques for the automated tumor detection system within the new discipline of computational pathology, which will be useful for the future practice of pathology and, more broadly, medical practice in general.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.57-64
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• 2018

In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.