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Clustering of 2D-Gel Images

  • Hur, Won
    • 한국생물공학회:학술대회논문집
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    • 2003.10a
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    • pp.746-749
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    • 2003
  • Alignment of 2D-gel images of biological samples can visualize the difference of expression profiles and also inform us candidates of protein spots to be further analyzed. However, comparison of two proteome images between case and control does not always successfully identify differentially expressed proteins due to sample-to-sample variation. Because of poor reproducibility of 2D-gel electrophoresis, sample-by-sample variations and inconsistent electrophoresis conditions, multiple number of 2D-gel image must be processed to align each other to visualize the difference of expression profiles and to deduce the protein spots differentially expressed with reliability. Alignment of multiple 2D-Gel images and their clustering were carried out by applying various algorithms and statistical methods. In order to align multiple images, multiresolution-multilevel algorithm was found out to be suitable for fast alignment and for distorted images. Clustering of 12 different images implementing a k-means algorithm gives a phylogenetic tree of distance map of the proteomes. Microsoft Visual C++ was used to implement the algorithms in this work.

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Scientific Approach to Fashion Websites Using Eye Trackers

  • Lee, Seunghee;Choi, Jung Won
    • Journal of Fashion Business
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    • v.24 no.6
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    • pp.63-79
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    • 2020
  • This study analyze consumers' unconscious visual attention to color and images of internet shopping malls by using eye-tracking method. Twenty-nine participants, including 15 females and 14 males, participated. The average ages of the male and female participants were 27.3 years and 27.7 years, respectively. Ten images of five layouts (multi-composition images, single-model images, gender-composed images, videos, and moving banner images) of internet shopping malls were shown on an eye-tracker computer screen. Quantitative analyses of the eye-tracking responses were conducted. SPSS was used to analyze the descriptive characteristics and to conduct an independent-sample t-test, along with an ANOVA. The data analysis showed that the image area generally had the shortest time to first fixation (TFF), the longest duration of fixation (DOF), the highest number of fixations (NOF), and the highest numbers of revisits(NOR).Notably, visual attention towards female models was high among various images. The results can be used to improve credibility and design online shopping layout with a scientific evidence that helps consumers through their purchase decisions.

Reduction of Seam Line Using an FIR Filter in Spatially Compounded Ultrasonic Diagnostic Images (공간합성된 초음파 의료영상에서 FIR 필터를 이용한 심라인 감소방법)

  • Choi, Myoung Hwan
    • Journal of Industrial Technology
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    • v.28 no.B
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    • pp.129-133
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    • 2008
  • A method to reduce seam line artifact in spatial compounding of ultrasonic images is presented. Spatial compounding is a speckle reducing imaging technique in which a number of ultrasound images of a given target that have been obtained from multiple view angles are combined into a single compounded image by combining the data received from each data point in the compounded image. Since different view angle results in different view area, and the images of different view arms are combined into an image, the compounded image consists of regions with different signal to noise ratio, and the boundary lines between these regions are visible as seam lines in the compounded images. In this paper, we present an algorithm that reduces the visibility of this seam line in the spatially compounded images. Design procedure for a FIH filter is described and the results of applying the filter to in-vivo ultrasonic images are analyzed.

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Reproducibility of Lateral Cephalometric Landmarks According to Radiographic Image Enhancement (방사선상 enhancement 정도에 따른 측모두부방사선규격사진 계측점 설정의 재현도)

  • Ryu, Hwang-Sog;Hwang, Hyeon-Shik
    • The korean journal of orthodontics
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    • v.32 no.1 s.90
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    • pp.59-69
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    • 2002
  • The purpose of this study was to evaluate the reproducibility of lateral cephalometric landmarks according to radiographic image enhancement, and to contribute to the identification of cephalometric landmarks. Lateral cephalograms of ten individuals were taken and stored into computer. The images were then enhanced up to four grades by Quick Ceph Image Pro$^{TM}$ on condition that the gray-scale equalization number was 50 and the detail enhancement number was 50. After thirty two landmarks were identified on monitor images by five observers, the deviations from the mean, the distances estimated between identified points and the mean point of five identified points, were evaluated for each landmark at each enhancement grade. Through the statistical analysis, following results were obtained. 1. In case of unenhanced radiographic images, the inter-observer reproducibility of the landmarks showed a large variation. 2. The comparison of deviation from the mean according to the degree of radiographic image enhancement for each landmark showed that the inter-observer reproducibility was significantly different at 5 landmarks. 3. The landmark of pterygomaxillary fissure showed higher reproducibility at enhancement grade 1 and 2 images than at unenhanced images. So did the landmark of posterior nasal spine at enhancement grade 1 images, and the landmark of menton at enhancement grade 2, 3 and 4 images respectively. The above results suggest that the reproducibility of some landmarks can be increased by radiographic image enhancement during the identification of the lateral cephalometric landmarks on the monitor.

Metal artifact production and reduction in CBCT with different numbers of basis images

  • Queiroz, Polyane Mazucatto;Santaella, Gustavo Machado;Groppo, Francisco Carlos;Freitas, Deborah Queiroz
    • Imaging Science in Dentistry
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    • v.48 no.1
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    • pp.41-44
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    • 2018
  • Purpose: To evaluate the effect of different numbers of basis images and the use of metal artifact reduction (MAR) on the production and reduction of artifacts in cone-beam computed tomography images. Materials and Methods: An acrylic resin phantom with a metal alloy sample was scanned, with 450 or 720 basis images and with or without MAR. Standard deviation values for the test areas (around the metal object) were obtained as a way of measuring artifact production. Two-way analysis of variance was used with a 5% significance level. Results: There was no significant difference in artifact production among the images obtained with different numbers of basis images without MAR (P=.985). MAR significantly reduced artifact production in the test areas only in the protocol using 720 basis images (P=.017). The protocol using 450 basis images with MAR showed no significant difference in artifact production when compared to the protocol using 720 basis images with MAR (P=.579). Conclusion: Protocols with a smaller number of basis images and with MAR activated are preferable for minimizing artifact production in tomographic images without exposing the patient to a greater radiation dose.

Fiber orientation distribution of reinforced cemented Toyoura sand

  • Safdar, Muhammad;Newson, Tim;Waseem, Muhammad
    • Geomechanics and Engineering
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    • v.30 no.1
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    • pp.67-73
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    • 2022
  • In this study, the fiber orientation distribution (FOD) is investigated using both micro-CT (computerized tomography) and image analysis of physically cut specimens prepared from Polyvinyl Alcohol (PVA) fiber reinforced cemented Toyoura sand. The micro-CT images of the fiber reinforced cemented sand specimens were visualized in horizontal and vertical sections. Scans were obtained using a frame rate of two frames and an exposure time of 500 milliseconds. The number of images was set to optimize and typically resulted in approximately 3000 images. Then, the angles of the fibers for horizontal sections and in vertical section were calculated using the VGStudio MAX software. The number of fibers intersecting horizontal and vertical sections are counted using these images. A similar approach was used for physically cut specimens. The variation of results of fiber orientation between micro-CT scans and visual count were approximately 4-8%. The micro-CT scans were able to precisely investigate the fiber orientation distribution of fibers in these samples. The results show that 85-90% of the PVA fibers are oriented between ±30° of horizontal, and approximately 95% of fibers have an orientation that lies within ±45° of the horizontal plane. Finally, a comparison of experimental results with the generalized fiber orientation distribution function 𝜌(θ) is presented for isotropic and anisotropic distribution in fiber reinforced cemented Toyoura sand specimens. Experimentally, it can be seen that the average ratio of the number of fibers intersecting the finite area on a vertical plane to number of fibers intersecting the finite area on a horizontal plane (NVtot/NHtot) cut through a sample varies from 2.08 to 2.12 (an average ratio of 2.10 is obtained in this study). Based up on the analytical predictions, it can be seen that the average NVtot/NHtot ratio varies from 2.13 to 2.17 for varying n values (an average ratio of 2.15).

Recognizing F5-like stego images from multi-class JPEG stego images

  • Lu, Jicang;Liu, Fenlin;Luo, Xiangyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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    • pp.4153-4169
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    • 2014
  • To recognize F5-like (such as F5 and nsF5) steganographic algorithm from multi-class stego images, a recognition algorithm based on the identifiable statistical feature (IDSF) of F5-like steganography is proposed in this paper. First, this paper analyzes the special modification ways of F5-like steganography to image data, as well as the special changes of statistical properties of image data caused by the modifications. And then, by constructing appropriate feature extraction sources, the IDSF of F5-like steganography distinguished from others is extracted. Lastly, based on the extracted IDSFs and combined with the training of SVM (Support Vector Machine) classifier, a recognition algorithm is presented to recognize F5-like stego images from images set consisting of a large number of multi-class stego images. A series of experimental results based on the detection of five types of typical JPEG steganography (namely F5, nsF5, JSteg, Steghide and Outguess) indicate that, the proposed algorithm can distinguish F5-like stego images reliably from multi-class stego images generated by the steganography mentioned above. Furthermore, even if the types of some detected stego images are unknown, the proposed algorithm can still recognize F5-like stego images correctly with high accuracy.

Tomosynthesis Feasibility Study for Visualization of Interiors of Wood Columns Surrounded with Walls

  • LEE, Jun Jae;KIM, Chul-Ki
    • Journal of the Korean Wood Science and Technology
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    • v.50 no.4
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    • pp.246-255
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    • 2022
  • The need for non-destructive testing and evaluation of Korean traditional wooden buildings is increasing because of their widespread deterioration. Among all types of deterioration, termite damage in wooden columns is the most difficult to detect with the naked eye because it starts inside the wood, and the initial deterioration is small. X-ray computed tomography (CT) is the best technology to investigate the inner state of wood that has less damage, but applying it to wooden columns between walls is challenging. Therefore, the feasibility of tomosynthesis, which is a method to reconstruct a coronal section of a subject with a few X-ray projections from a limited angle of rotation, was studied as an alternative to CT. Pine (P. densiflora) with three artificial holes was prepared as a specimen to evaluate the quality of reconstructed tomosynthesis images according to the different number of projections. The quality of the tomosynthesis images in the in-focus plane was evaluated using the contrast-to-noise ratios, while a vertical resolution between the images was assessed by determining the artificial spread function. The quality of the tomosynthesis image in the in-focus plane increased as the number of projections increased and then remained constant as the number of projections reached 21 or over. In the case of vertical resolution, there was no significant difference when 21 projections or more were used to reconstruct the images. A distinct difference between coronal section images was found when the distance was more than 10 mm from one plane to another plane.

Performance Evaluation of ResNet-based Pneumonia Detection Model with the Small Number of Layers Using Chest X-ray Images (흉부 X선 영상을 이용한 작은 층수 ResNet 기반 폐렴 진단 모델의 성능 평가)

  • Youngeun Choi;Seungwan Lee
    • Journal of radiological science and technology
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    • v.46 no.4
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    • pp.277-285
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    • 2023
  • In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

Study to safely transmit encrypted images from various noises in space environment

  • Kim, Ki-Hwan;Lee, Hoon Jae
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.11
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    • pp.97-104
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    • 2020
  • In this paper, we propose a random number generator PP(PingPong256) and a shuffle technique to improve the problem that the encrypted image is damaged due to a lot of noise by the channel coding of wireless communication recommended in the special environment of space. The PP can constantly generate random numbers by entering an initial value of 512 bits. Random numbers can be encrypted through images and exclusive logical computations. Random numbers can be encrypted through images and exclusive logical computations. The shuffle technique randomly rearranges the image pixel positions while synchronizing the image pixel position and the random number array position and moving the random number arrangement in ascending order. Therefore, the use of PP and shuffle techniques in channel coding allows all pixels to be finely distributed and transmit high-quality images even in poor transmission environments.