• Archives of Plastic Surgery
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• 제34권5호
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• pp.605-610
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• 2007

Purpose: Facial trauma is increasing along with increasing popularity in sports, and increasing exposure to crimes or traffic accidents. Compared to the 3D CT of 1990s, the latest CT has made significant improvement thus resulting in higher accuracy of diagnosis. The objective of this study is to compare 64 channel 3 dimensional volume CT(3D VCT) with conventional 3D CT in the diagnosis and treatment of facial bone fractures. Methods: 45 patients with facial trauma were examined by 3D VCT from Jan. 2006 to Feb. 2007. 64 channel 3D VCT which consists of 64 detectors produce axial images of 0.625 mm slice and it scans 175 mm per second. These images are transformed into 3 dimensional image using software Rapidia 2.8. The axial image is reconstructed into 3 dimensional image by volume rendering method. The image is also reconstructed into coronal or sagittal image by multiplanar reformatting method. Results: Contrasting to the previous 3D CT which formulates 3D images by taking axial images of 1-2 mm, 64 channel 3D VCT takes 0.625 mm thin axial images to obtain full images without definite step ladder appearance. 64 channel 3D VCT is effective in diagnosis of thin linear bone fracture, depth and degree of fracture deviation. Conclusion: In its expense and speed, 3D VCT is superior to conventional 3D CT. Owing to its ability to reconstruct full images regardless of the direction using 2 times higher resolution power and 4 times higher speed of the previous 3D CT, 3D VCT allows for accurate evaluation of the exact site and deviation of fine fractures.

• Journal of information and communication convergence engineering
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• 제8권6호
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• pp.645-650
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• 2010

In this paper, we present the effect of binocular cues which plays crucial role for the visualization of a stereoscopic or 3D image. This study is useful in extracting depth and disparity information by image processing technique. A linear relation between the object distance and the image distance is presented to discuss the cause of cybersickness. In the experimental results, three dimensional view of the depth map between the 2D images is shown. A median filter is used to reduce the noises available in the disparity map image. After the median filter, two filter algorithms such as 'Gabor' filter and 'Canny' filter are tested for disparity visualization between two images. The 'Gabor' filter is to estimate the disparity by texture extraction and discrimination methods of the two images, and the 'Canny' filter is used to visualize the disparity by edge detection of the two color images obtained from stereoscopic cameras. The 'Canny' filter is better choice for estimating the disparity rather than the 'Gabor' filter because the 'Canny' filter is much more efficient than 'Gabor' filter in terms of detecting the edges. 'Canny' filter changes the color images directly into color edges without converting them into the grayscale. As a result, more clear edges of the stereo images as compared to the edge detection by 'Gabor' filter can be obtained. Since the main goal of the research is to estimate the horizontal disparity of all possible regions or edges of the images, thus the 'Canny' filter is proposed for decipherable visualization of the disparity.

• 대한원격탐사학회지
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• 제36권4호
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• pp.515-525
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• 2020

This study investigates the potential of bidirectional long short-term memory (Bi-LSTM) for efficient modeling of temporal information in crop classification using multitemporal remote sensing images. Unlike unidirectional LSTM models that consider only either forward or backward states, Bi-LSTM could account for temporal dependency of time-series images in both forward and backward directions. This property of Bi-LSTM can be effectively applied to crop classification when it is difficult to obtain full time-series images covering the entire growth cycle of crops. The classification performance of the Bi-LSTM is compared with that of two unidirectional LSTM architectures (forward and backward) with respect to different input image combinations via a case study of crop classification in Anbadegi, Korea. When full time-series images were used as inputs for classification, the Bi-LSTM outperformed the other unidirectional LSTM architectures; however, the difference in classification accuracy from unidirectional LSTM was not substantial. On the contrary, when using multitemporal images that did not include useful information for the discrimination of crops, the Bi-LSTM could compensate for the information deficiency by including temporal information from both forward and backward states, thereby achieving the best classification accuracy, compared with the unidirectional LSTM. These case study results indicate the efficiency of the Bi-LSTM for crop classification, particularly when limited input images are available.

• Journal of Radiation Protection and Research
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• 제40권1호
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• pp.17-24
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• 2015

To improve accuracy of dose calculation on kilovoltage cone beam computed tomography (kV CBCT) images, a custom-made phantom was fabricated to acquire an accurate CT number to electron density curve by full scatter of cone beam x-ray. To evaluate the dosimetric accuracy, 9 volumetric modulated arc therapy (VMAT) plans for head and neck (HN) cancer and 9 VMAT plans for lung cancer were generated with an anthropomorphic phantom. Both CT and CBCT images of the anthropomorphic phantom were acquired and dose-volumetric parameters on the CT images with CT density curve (CTCT), CBCT images with CT density curve ($CBCT_{CT}$) and CBCT images with CBCT density curve ($CBCT_{CBCT}$) were calculated for each VMAT plan. The differences between $CT_{CT}$ vs. $CBCT_{CT}$ were similar to those between $CT_{CT}$ vs. $CBCT_{CBCT}$ for HN VMAT plans. However, the differences between $CT_{CT}$ vs. $CBCT_{CT}$ were larger than those between $CT_{CT}$ vs. $CBCT_{CBCT}$ for lung VMAT plans. Especially, the differences in $D_{98%}$ and $D_{95%}$ of lung target volume were statistically significant (4.7% vs. 0.8% with p = 0.033 for $D_{98%}$ and 4.8% vs. 0.5% with p = 0.030 for $D_{95%}$). In order to calculate dose distributions accurately on the CBCT images, CBCT density curve generated with full scatter condition should be used especially for dose calculations in the region of large inhomogeneity.

• 대한원격탐사학회지
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• 제38권6_4호
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• 디지털콘텐츠학회 논문지
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• 제16권5호
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• pp.717-725
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• 2015

전립선 영상은 비용이 상대적으로 저렴한 경직장 초음파 영상을 이용하여 전립선 진단에 많이 사용된다. 경직장 초음파 영상은 3차원으로 촬영되어 여러 장으로 하나의 진단 단위가 만들어 진다. 의사는 진단을 위해 2차원 영상을 순서대로 모니터에 표시하여 볼 수도 있고, 3차원의 영상을 볼 수도 있다. 2차원 영상은 원 영상을 그대로 출력하면 되지만, 3차원 영상은 다양한 각도에서 보이기도 하고, 내부의 어떤 면을 자른 형태로도 보여야 하므로 정확하게 전립선과 배경을 구분하여야 한다. 특히 경계를 구분할 때, 전립선의 중간 부분은 상대적으로 구분하기 쉬우나, 기저부와 첨단부는 불확실한 부분이 많으므로 경계를 구분하기기 매우 어렵다. 이에, 본 논문은 평균 형상 모델을 적용하여 전립선 경계를 추출하는 방법을 제안하고, 실험을 통하여 기존의 방법에 비해 우수함을 보인다.

• 감성과학
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• 제14권3호
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• pp.385-394
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• 2011

본 연구의 목적은 20대 표준체형 여성을 대상으로 하여, 소재에 따른 플레어 스커트의 실제착의와 가상착의에 따른 시각적 이미지를 비교 분석하고, 시각적 이미지와 역학적 특성간의 상관관계를 분석하는 데에 있다. 본 연구는 드레이프 특성이 확연히 다른 5종류의 소재를 사용하였다. 실험에 사용되어진 플레어 스커트의 실제착의와 가상착의의 이미지는 사진으로 제공되었으며, 피설문자는 20대의 의류학 전공의 여성이었다. 자료의 분석은 SPSS Ver.12.0 프로그램을 사용하여 통계 처리하였으며, 연구 문제별로 요인분석, 일원변량분석(One way ANOVA), T 검정(t-test), 던컨테스트(Duncan test)를 실시하였다. 시각적 이미지에 대한 요인분석 결과 '드레이프성', '매력성', '신체 보정성', '부피감', '활동성' 의 총 5 가지 요인이 분석되었다. 시각적 이미지중 '부피감'의 경우 G, 무게, 두께와 같은 역학적 특성들과 밀접한 상관관계를 나타냈으며, 3차원 의복 시뮬레이션과 실제착의간의 시각적 이미지는 소재에 따라 유의한 차이점을 나타냈는데, 실크나 폴리에스터 소재와 면, 린넨, 양모소재간 이미지 차이는 소재의 무게와 두께에 따라 영향을 많이 받는 것으로 나타났다.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2006년도 한국우주과학회보 제15권2호
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• pp.81-81
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• 2006

• 천문학회보
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• 제31권2호
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• pp.73.1-73.1
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• 2006

• 대한가정학회지
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• 제49권1호
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• pp.121-133
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• 2011

This research was designed to compare the subjective evaluation of texture image and preference between offline and online by structural characteristics of women' jacket fabrics for spring and summer. 78 participants evaluated the sensibility image and preference of various fabrics. The data were analysed by factor analysis, t-test, Pearson's productive correlation, regression, and multi dimensional scale. The results were as follows: Sensibility image factors of women' jacket fabrics were 'classic' 'sophisticated' 'natural' 'characteristic' and 'practical'. Between offline and online, sensibility images showed no differences. In sensibility images, 'classic'-'sophisticated', 'natural'-'practical', and 'practical'-'characteristic' images showed significant correlation. By analyzing the contribution of fabric structure on sensibility images, density affected on the 'classic' image offline and online. By the results of regression analysis, thickness, density and weave affected on the tactile preference. In sensibility images, 'classic', 'sophisticated' 'characteristic' images were the influencing factor. 'Sophisticated', 'natural', 'characteristic' and 'practical' images affected on the purchase preference.