• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.991-999
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• 2003

In this paper, we proposed image acquisition techniques that can reflect anatomical airway information lot breath change by EBCT Also, we proposed new method to detect automatically boundary of inner airway for acquired slice images using this image acquisition technology. We confirmed that new method detects boundary of inner airway effectively through computer simulation that apply image data about each slice position of airway. And, we could see change for cross section area of inner airway by time change. Therefore, we think that proposed method can utilize on quantitative analysis in clinical field.

• Journal of Korea Multimedia Society
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• v.21 no.7
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• pp.764-771
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• 2018

In this paper, we propose a high-quality image acquisition algorithm using only a single image, which the high-quality image is normally referred as HDR ones. In order to acquire the HDR image, conventional methods need many images having different exposure values at the same scene and should delicately adjust the color values for a bit-expansion or an exposure fusion. Thus, they require considerable calculations and complex structures. Therefore, the proposed algorithm suggests a completely new approach using one image for the high-quality image acquisition by applying statistical difference and histogram manipulation, or histogram specification, techniques. The techniques could control the pixel's statistical distribution of the input image into the desired one through the local and the global modifications, respectively. As the result, the quality of the proposed algorithm is better than those of conventional methods implemented in commercial image editing softwares.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.39-45
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• 2017

In this paper, we propose three compensation methods to solve problems in high-resolution airborne infrared camera and to improve long-range target information acquisition performance. First, image motion and temporal noise reduction technique which is caused by atmospheric turbulence. Second, thermal blurring image correction technique by imperfect performance of NUC(Non Uniformity Correction) or raising the internal temperature of the camera. Finally, DRC(Dynamic Range Compression) and flicker removing technique of 14bits HDR(High Dynamic Range) infrared image. Through this study, we designed techniques to improve the acquisition performance of long-range target information of high-resolution airborne infrared camera, and compared and analyzed the performance improvement result with implemented images.

• Progress in Medical Physics
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• v.31 no.3
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• pp.81-98
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• 2020

This review aims to provide a brief, comprehensive overview of advanced technologies of nuclear medicine physics, with a focus on recent developments from both hardware and software perspectives. Developments in image acquisition/reconstruction, especially the time-of-flight and point spread function, have potential advantages in the image signal-to-noise ratio and spatial resolution. Modern detector materials and devices (including lutetium oxyorthosilicate, cadmium zinc tellurium, and silicon photomultiplier) as well as modern nuclear medicine imaging systems (including positron emission tomography [PET]/computerized tomography [CT], whole-body PET, PET/magnetic resonance [MR], and digital PET) enable not only high-quality digital image acquisition, but also subsequent image processing, including image reconstruction and post-reconstruction methods. Moreover, theranostics in nuclear medicine extend the usefulness of nuclear medicine physics far more than quantitative image-based diagnosis, playing a key role in personalized/precision medicine by raising the importance of internal radiation dosimetry in nuclear medicine. Now that deep-learning-based image processing can be incorporated in nuclear medicine image acquisition/processing, the aforementioned fields of nuclear medicine physics face the new era of Industry 4.0. Ongoing technological developments in nuclear medicine physics are leading to enhanced image quality and decreased radiation exposure as well as quantitative and personalized healthcare.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.195-203
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• 2022

Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

• Journal of the Korean Society for information Management
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• v.16 no.4
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• pp.53-74
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• 1999

This paper describes concept mapping techniques for eliciting and representing knowledge. Concept mapping techniques range from very informal to very formal. Informal concept mapping techniques are usually very easy to use and understand for humans, but not for computers. Formal concept mapping techniques are computational, but humans usually find them hard to understand and use. A knowledge acquisition and representation tools which handle both kinds, and the transition from informal to formal, would be very useful. It is proposed that concept maps be regarded as basic components of any knowledge-based system, complementing text and image with formal and informl active diagrams.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.252-265
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• 2021

Cardiac magnetic resonance imaging (MRI) serves as a clinical gold-standard non-invasive imaging technique for the assessment of global and regional cardiac function. Conventional cardiac MRI is limited by the long acquisition time, the need for ECG gating and/or long breathhold, and insufficient spatiotemporal resolution. Real-time cardiac cine MRI refers to high spatiotemporal cardiac imaging using data acquired continuously without synchronization or binning, and therefore of potential interest in overcoming the limitations of conventional cardiac MRI. Novel acquisition and reconstruction techniques must be employed to facilitate real-time cardiac MRI. The goal of this study is to discuss methods that have been developed for real-time cardiac MRI. In particular, we classified existing techniques into two categories based on the use of non-iterative and iterative reconstruction. In addition, we present several research trends in this direction, including deep learning-based image reconstruction and other advanced real-time cardiac MRI strategies that reconstruct images acquired from real-time free-breathing techniques.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.13-17
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• 2004

In order to measure the retina thickness, the retina photographing system and the multi-channel high speed image data acquisition system is developed. This system requires the optical processing techniques and the high speed image processing techniques. The HeNe laser beam is projected the retina in artificial eye and then we sensed the reflected laser signal using APD array. The laser projection system on retina using optical instruments is implemented. In order to project the plane laser beam on retina, laser photographing system used the polygon mirror for horizontal scanning and the galvano mirror for vertical scanning. We acquired retina images in each channel of APD array, transferred computer using PCI interface the image data after real-time A/D converting.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.429-431
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• 2002

Metabolic analysis of biological tissues, the interventional radiology in MRT (Magnetic Resonance Treatment) and for clinical diagnoses, representation of 4-Dimensional (4D) structural information (x,y,z,t) of biological tissues is required. This paper discusses image representation techniques for those 4D MR Images. We have proposed an image reconstruction method for ultra-fast 3D MRI. It is based on image interpolation and prediction of un-acquired pictorial data in both of the real and the k-space (the acquisition domain in MRI). A 4D MR image is reconstructed from only two 3D MR images and acquired a few echo signals that are optimized by prediction of the tissue motion. This prediction can be done by the phase of acquired echo signal is proportioned to the tissue motion. On the other hand, reconstructed 4D MR images are represented as a 3D-movie by using computer graphics techniques. Rendered tissue surfaces and/or ROIs are displayed on a CRT monitor. It is represented in an arbitrary plane and/or rendered surface with their motion. As examples of the proposed representation techniques, the finger and the lung motion of healthy volunteers are demonstrated.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1229-1239
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• 2022

Recently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI fields. In particular, AI models for improving the efficiency of the image acquisition process and the quality of reconstructed images are being actively developed by the MR research community. AI is expected to further reduce acquisition times in various MRI protocols used in clinical practice when compared to current parallel imaging techniques. Additionally, AI can help with tasks such as planning, parameter optimization, artifact reduction, and quality assessment. Furthermore, AI is being actively applied to automate MR image analysis such as image registration, segmentation, and object detection. For this reason, it is important to consider the effects of protocols or devices in MR image analysis. In this review article, we briefly introduced issues related to AI application of MR image acquisition and reconstruction.