• Design Convergence Study
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• v.14 no.1
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• pp.83-98
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• 2015

This study will examine the visual composition by which Secretly Greatly, in a circumstance that even the good original Manhwas or Webtoon have not made a hit on the market until now, could attract the spectator, in other word, illustrate the analogousness of the images through analysing visual texts. The study draw, first of all, a meaning of the box office performance caused by analogousness of image, that is similarity between the webtoon and film. In addition, the study will come up with an answer to the question that the webtoon, not in a temporary trend but in a sustainable form, can make itself develop. For this, the study suggests a meaning, worth and importance of the transformation, analysing visual components of a webtoon to film adaptation, Secretly Greatly. It primarily ranges over visual components, mise-en-scène identified with its expression formula, frame to frame changes and colour and tone. The examination sets the cinema's visual expression manner against the webtoon's on their concrete components: the size of scene, movement, color and tone, narrative condition and its background, spatial composition and depth, contrast, expression manner and disposition manner.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.474-476
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• 2021

Glioblastoma is the most common brain malignancies arising from glial cells. Early diagnosis and treatment plan establishment are important, and cancer is diagnosed mainly through T1CE imaging through injection of a contrast agent. However, the risk of injection of gadolinium-based contrast agents is increasing recently. Region segmentation that marks cancer regions in medical images plays a key role in CAD systems, and deep neural network models for synthesizing new images are also being studied. In this study, we propose a model that simultaneously learns the generation of T1CE images and segmentation of cancer regions. The performance of the proposed model is evaluated using similarity measurements including mean square error and peak signal-to-noise ratio, and shows average result values of 21 and 39 dB.

• Journal of the Korea Computer Graphics Society
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• v.30 no.1
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• pp.11-17
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• 2024

Lung cancer segmentation in chest CT images is challenging due to the varying sizes of tumors and the presence of surrounding structures with similar intensity values. To address these issues, we propose a lung cancer segmentation network that incorporates deep supervision and utilizes UNet3+ as the backbone. Additionally, we propose a hybrid lesion focal loss function comprising three components: pixel-based, region-based, and shape-based, which allows us to focus on the smaller tumor regions relative to the background and consider shape information for handling ambiguous boundaries. We validate our proposed method through comparative experiments with UNet and UNet3+ and demonstrate that our proposed method achieves superior performance in terms of Dice Similarity Coefficient (DSC) for tumors of all sizes.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.29-38
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• 2024

After Transcatheter Aortic Valve Replacement (TAVR), comprehensive management of complications, including the need for Permanent Pacemaker Implantation (PPI), is crucial, increasing the demand for accurate prediction models. Departing from traditional image-based methods, this study developed an optimal PPI prediction model based on ECG data using the XGBoost algorithm. Focusing on ECG signals like DeltaPR and DeltaQRS as key indicators, the model effectively identifies the correlation between conduction disorders and PPI needs, achieving superior performance with an AUC of 0.91. Validated using data from two hospitals, it demonstrated a high similarity rate of 95.28% in predicting PPI from ECG characteristics. This confirms the model's effective applicability across diverse hospital data, establishing a significant advancement in the development of reliable and practical PPI prediction models with reduced dependence on human intervention and costly medical imaging.

• Korean Circulation Journal
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• v.54 no.1
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• pp.30-39
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• 2024

Background and Objectives: Intravascular ultrasound (IVUS) evaluation of coronary artery morphology is based on the lumen and vessel segmentation. This study aimed to develop an automatic segmentation algorithm and validate the performances for measuring quantitative IVUS parameters. Methods: A total of 1,063 patients were randomly assigned, with a ratio of 4:1 to the training and test sets. The independent data set of 111 IVUS pullbacks was obtained to assess the vessel-level performance. The lumen and external elastic membrane (EEM) boundaries were labeled manually in every IVUS frame with a 0.2-mm interval. The Efficient-UNet was utilized for the automatic segmentation of IVUS images. Results: At the frame-level, Efficient-UNet showed a high dice similarity coefficient (DSC, 0.93±0.05) and Jaccard index (JI, 0.87±0.08) for lumen segmentation, and demonstrated a high DSC (0.97±0.03) and JI (0.94±0.04) for EEM segmentation. At the vessel-level, there were close correlations between model-derived vs. experts-measured IVUS parameters; minimal lumen image area (r=0.92), EEM area (r=0.88), lumen volume (r=0.99) and plaque volume (r=0.95). The agreement between model-derived vs. expert-measured minimal lumen area was similarly excellent compared to the experts' agreement. The model-based lumen and EEM segmentation for a 20-mm lesion segment required 13.2 seconds, whereas manual segmentation with a 0.2-mm interval by an expert took 187.5 minutes on average. Conclusions: The deep learning models can accurately and quickly delineate vascular geometry. The artificial intelligence-based methodology may support clinicians' decision-making by real-time application in the catheterization laboratory.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.51-63
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• 2011

The purpose of this study is to create a landscape image that considers the selection of techniques that can enhance landscape reproduction in streetscape evaluation using 3 dimensional simulations and to evaluate ways to verify similarities and the psychological changes on the part of users by season. In the comparison of technique, the Low(apply normal map) technique was selected for the natural representation of trees in a near and middle view and the Plane technique was selected for the distant view. As the result of the verification, all indicators of physical similarity were evaluated over 4.50 points and most indicators of psychological similarity were found to have no difference except for indicators of 'disordered orderly' and 'dirty - clean'. According to the results of analyzing the landscape simulation by season, images of 'bright', 'beautiful', and 'static', etc., were evaluated high for the spring streetscape. The images of 'open', 'refresh', and 'animate' appeared high in summer and images of 'warm' and 'dark' were found to be high in fall. On the other hand, all images were evaluated as low except for the 'orderly' image. In the preference of streetscape by season, summer and spring were highly preferred at 5.01 and 4.98 with winter as the lowest at 3.48. As the results of the analysis of preference factor, the spring streetscape was found to be a major influence in preference by 0.540 in 'aesthetics'. In the case of summer, 'order' was found to be high at 0.417 while influences in preference included 'variety' and 'aesthetics' in fall and 'variety', 'aesthetics', and 'order' in winter. A determination of suitable spatial planning using a comparative analysis of various city streets will be enabled through the methods of this study.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.2
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• pp.161-169
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• 2016

Purpose : To quantify the inter-fractional variation in prostate displacement and their dosimetric effects for prostate cancer treatment. Materials and Methods : A total of 176 daily cone-beam CT (CBCT) sets acquired for 6 prostate cancer patients treated with volumetric-modulated arc therapy (VMAT) were retrospectively reviewed. For each patient, the planning CT (pCT) was registered to each daily CBCT by aligning the bony anatomy. The prostate, rectum, and bladder were delineated on daily CBCT, and the contours of these organs in the pCT were copied to the daily CBCT. The concordance of prostate displacement, deformation, and size variation between pCT and daily CBCT was evaluated using the Dice similarity coefficient (DSC). Results : The mean volume of prostate was 37.2 cm3 in the initial pCT, and the variation was around ${\pm}5%$ during the entire course of treatment for all patients. The mean DSC was 89.9%, ranging from 70% to 100% for prostate displacement. Although the volume change of bladder and rectum per treatment fraction did not show any correlation with the value of DSC (r=-0.084, p=0.268 and r=-0.162, p=0.032, respectively), a decrease in the DSC value was observed with increasing volume change of the bladder and rectum (r=-0.230,p=0.049 and r=-0.240,p=0.020, respectively). Conclusion : Consistency of the volume of the bladder and rectum cannot guarantee the accuracy of the treatment. Our results suggest that patient setup with the registration between the pCT and daily CBCT should be considered aligning soft tissue.

• Journal of Science of Art and Design
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• v.3
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• pp.87-144
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• 2001

This study looks into historical genealogy of autonomy in art criticism on modernism and presents the view of the judgment and correction about that. A matter of autonomy in art appeared in the attempt to totally reconsider and upset the theory of 'Mimesis' or 'Representation' which was the basis of traditional aesthetic theory. In the traditional theory of representation, they assumed primary image exists first and then tried to obtain visual similarity to it through art works. However, in the theory of autonomy in modernism, they maintained the reduction to pure form' or medium', regarding what art works represents and how similar to primary image are not the true essence of art. In the early 20th century, C. Bell laid the foundation stone of the theory of Formalism', providing that a matter of autonomy is significant form', which is the combination of lines and colors Aesthetic autonomy theory came to a climax by C. Greenberg, who systemized art criticism on modernism in the middle 20th century. According to his theory, the pursuit of the essence of form resulted in the specificity of medium' and flatness. They thought that the autonomy of art would be achieved by eliminating outward social factors from art works. This theory ended by Minimalism preventing the instructive function of art work and only emphasizing its material property. Since the middle 20th century, the autonomy theory was confronted with the limit and intense attack because it resulted in this fixed canon and materialism, so they began laying emphasis on those extrinsic factors around art works such as human life, society, history, and so on. This study focuses on arguing and complementing the limit of autonomy such as the adhesive and fixed canon, and then defining the more dynamic area of it. For this, first, I introduced the view of T. J. Clark and T. Crow who criticized the aesthetic autonomy theory. They denied the transcendental structure of form, and found form only in the association with substantial life and society. And they insisted the dynamism of form by emphasizing form as a result of negation insisted by avant-garde. Second, I researched the view of A. C, Danto and M. Fried, who complemented the traditional autonomy theory. They made autonomy emerge from the fixation of form like flatness through connecting essentialism with historical view. In conclusion, I insist that autonomic position of art make it possible to connect or mediate between material form and human or social elements. Therefore, autonomy should not be reduced to the axis of form or that of society but make interaction between two heterogeneous axes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2315-2321
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• 2013

This study attempt to develope and suggest a new, minimize side effects process for calculate a time to peak enhancement of contrast level by using blood flow instead of current mathematical process. We conducted a studies 127 patients who performed the CE MRA by using test-contrast inject way. We used measurements of a contrast inflow time and time to peak enhancement of contrast level of each cerebrovascular branch for similarity of witch cerebrovascular branch calculate a time to peak enhancement of contrast level by using blood flow in image compared with calculation a time to peak enhancement of contrast level by using current mathematical process after contrast enhancement. In this study, confidence interval were used if the variable is continuous variable; there is differences between 4 groups exist but in group 1, there is no difference with time in peak enhancement of contrast level by using mathematical method to inflow time in sinus sigmoideus. it was significant statistically, in addition there was significant low heterogeneity in Bland Altman plot. Thus, apply a new calculate a time to peak enhancement of contrast level by using blood flow method will minimize damage caused by side effect, maintain quality of image, easy and fast access. It should provide a space for the exchange of current calculate a time to peak enhancement of contrast level by using mathematical process.