• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.222-228
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• 2023

This study aimed to analyze the applicability of the improved median filter in positron emission tomography (PET)/magnetic resonance (MR) fusion images based on parallel imaging using generalized autocalibrating partially parallel acquisition (GRAPPA). In this study, a PET/MR fusion imaging system based on a 3.0T magnetic field and ¹⁸F radioisotope were used. An improved median filter that can set a mask of the median value more efficiently than before was modeled and applied to the acquired image. As quantitative evaluation parameters of the noise level, the contrast to noise ratio (CNR) and coefficient of variation (COV) were calculated. Additionally, no-reference-based evaluation parameters were used to analyze the overall image quality. We confirmed that the CNR and COV values of the PET/MR fusion images to which the improved median filter was applied improved by approximately 3.32 and 2.19 times on average, respectively, compared to the noisy image. In addition, the no-reference-based evaluation results showed a similar trend for the noise-level results. In conclusion, we demonstrated that it can be supplemented by using an improved median filter, which suggests the problem of image quality degradation of PET/MR fusion images that shortens scan time using GRAPPA.

• Journal of Applied and Pure Mathematics
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• v.5 no.5_6
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.3
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• pp.165-173
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• 2009

Nuclear cardiology in Korea is less active, compared to nuclear oncology, but it has been specialized and ramified. Lately, sophisticated nuclear cardiac imaging methods provide more convenience for patients. It is necessary to accurately estimate the recent progress in the imaging devices for nuclear cardiology. Myocardial perfusion imaging is a well established study to evaluate heart function. Myocardial perfusion SPECT and PET have been used for assessment of coronary artery disease with various radiopharmaceuticals. And of late, the development of advanced imaging devices - multi-pinhole technique and high definition imaging technique - and software made the scanning time shorter and expanded the application field. Therefore, it is required to review the nuclear cardiology hardware/software for the clinical practice and research. In this review, the characteristics about recently-developed SPECT/PET and software for nuclear cardiology are described. It is hoped that this information would contribute to improving the activity of nuclear cardiac research in Korea where the research for the fusion imaging combining a and nuclear imaging is drawing more attention.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.78-82
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• 2010

Purpose: Recently, South Korea has seen a rapidly increased incidence of both breast and thyroid cancers. As a result, the I-131 scan and lymphoscintigraphy have been performed more frequently. Although this type of diagnostic imaging is prominent in that visualizes pathological conditions, which is similar to previous nuclear diagnostic imaging techniques, there is not much anatomical information obtained. Accordingly, it has been used in different ways to help find anatomical locations by transmission scan, however the results were unsatisfactory. Therefore, this study aims to realize an imaging technique which shows more anatomical information through the fusion of gamma and realistic imaging. Materials and Methods: We analyzed the data from patients who were examined by the lymphoscintigraphy and I-131 additional scan by Symbia Gamma camera (SIEMENS) in the nuclear medicine department of the National Cancer Center from April to July of 2009. First, we scanned the same location in patients by using a miniature camera (R-2000) in hyVISION. Afterwards, we scanned by gamma camera. The data we obtained was evaluated based on the scanning that measures an agreement of gamma and realistic imaging by the Gamma Ray Tool fusion program. Results: The amount of radiation technicians and patients were exposed was generated during the production process of flood source and applied transmission scan. During this time, the radiation exposure dose of technicians was an average of 14.1743 ${\mu}Sv$, while the radiation exposure dose of patients averaged 0.9037 ${\mu}Sv$. We also confirmed this to matching gamma and realistic markers in fusion imaging. Conclusion: Therefore, we found that we could provide imaging with more anatomical information to clinical doctors by fusion of system of gamma and realistic imaging. This has allowed us to perform an easier method in which to reduce the work process. In addition, we found that the radiation exposure can be reduced from the flood source. Eventually, we hope that this will be applicable in other nuclear medicine studies. Therefore, in order to respect the privacy of patients, this procedure will be performed only after the patient has agreed to the procedure after being given a detailed explanation about the process itself and its advantages.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• Investigative Magnetic Resonance Imaging
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• v.24 no.3
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• pp.123-131
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• 2020

Purpose: Joint label fusion (JLF) is a popular multi-atlas-based segmentation algorithm, which compensates for dependent errors that may exist between atlases. However, in order to get good segmentation results, it is very important to set the several free parameters of the algorithm to optimal values. In this study, we first investigate the feasibility of a JLF algorithm for prostate segmentation in MR images, and then suggest the optimal set of parameters for the automatic prostate segmentation by validating the results of each parameter combination. Materials and Methods: We acquired T2-weighted prostate MR images from 20 normal heathy volunteers and did a series of cross validations for every set of parameters of JLF. In each case, the atlases were rigidly registered for the target image. Then, we calculated their voting weights for label fusion from each combination of JLF's parameters (r_pxy, r_pz, r_sxy, r_sz, β). We evaluated the segmentation performances by five validation metrics of the Prostate MR Image Segmentation challenge. Results: As the number of voxels participating in the voting weight calculation and the number of referenced atlases is increased, the overall segmentation performance is gradually improved. The JLF algorithm showed the best results for dice similarity coefficient, 0.8495 ± 0.0392; relative volume difference, 15.2353 ± 17.2350; absolute relative volume difference, 18.8710 ± 13.1546; 95% Hausdorff distance, 7.2366 ± 1.8502; and average boundary distance, 2.2107 ± 0.4972; in parameters of r_pxy = 10, r_pz = 1, r_sxy = 3, r_sz = 1, and β = 3. Conclusion: The evaluated results showed the feasibility of the JLF algorithm for automatic segmentation of prostate MRI. This empirical analysis of segmentation results by label fusion allows for the appropriate setting of parameters.

• Journal of radiological science and technology
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• v.42 no.5
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• pp.365-371
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• 2019

We have developed and applied a diagnostic Multi-Leaf Collimator (MLC) to optimized the X-ray field in medical imaging and the usefulness evaluated through the fusion of infrared image and X-ray image acquired by infrared camera. The hand and skull radiography with multi-leaf collimator(MLC) showed significant area dose reductions of 22.9% and 31.3% compared to ARC and leakage dose was compliant with KS A 4732. Also scattering doses of 50 cm and 100 cm showed a significant decrease to confirm the usefulness of MLC. It was confirmed that the fusion of infrared images with an adjustable degree of transparency was possible in the X-ray images. Therefore, fusion of anatomical information with physiological convergence is expected to contribute and improvement of diagnostic ability. In addition, the feasibility of convergence X-ray imaging and DITI devices and the possibility of driving MLC with infrared images were confirmed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.177-187
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• 2010

A MTG (Multimode Tracking and Guidance) system is employed to compensate for the limitations of individual seekers such as RF (Radio frequency) or IIR (Imaging Infra-red) and to improve the overall tracking and guidance performance in jamming, clutter, and adverse weather environments. In the MTG system, tracking filter, data association, and data fusion methods are important elements to maximize the effectiveness of precision homing missile guidance. This paper proposes the formulation of a Kalman filter for the estimation of line-of-sight rate from seeker measurements in missiles guided by proportional navigation. Also, we suggest the HPDA (Highest Probability Data Association) and data fusion methods of the MTG system for target tracking in the adverse environments. Mont-Carlo simulation is employed to evaluate the overall tracking performance and guidance accuracy.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.523-530
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• 2019

The purpose of this study was to obtain the K-edge images using a spectral CT system based on a photon-counting detector and implement the 3D fusion imaging using the conventional and spectral CT images. Also, we evaluated the clinical feasibility of the 3D fusion images though the quantitative analysis of image quality. A spectral CT system based on a CdTe photon-counting detector was used to obtain K-edge images. A pork phantom was manufactured with the six tubes including diluted iodine and gadolinium solutions. The K-edge images were obtained by the low-energy thresholds of 35 and 52 keV for iodine and gadolinium imaging with the X-ray spectrum, which was generated at a tube voltage of 100 kVp with a tube current of $500{\mu}A$. We implemented 3D fusion imaging by combining the iodine and gadolinium K-edge images with the conventional CT images. The results showed that the CNRs of the 3D fusion images were 6.76-14.9 times higher than those of the conventional CT images. Also, the 3D fusion images was able to provide the maps of target materials. Therefore, the technique proposed in this study can improve the quality of CT images and the diagnostic efficiency through the additional information of target materials.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.349-354
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• 2011

Passive millimeter wave imaging has the capability of detecting concealed objects under clothing. Also, passive millimeter imaging can obtain interpretable images under low visibility conditions like rain, fog, smoke, and dust. However, the image quality is often degraded due to low spatial resolution, low signal level, and low temperature resolution. This paper addresses image registration and fusion between passive millimeter images and visual images. The goal of this study is to combine and visualize two different types of information together: human subject's identity and concealed objects. The image registration process is composed of body boundary detection and an affine transform maximizing cross-correlation coefficients of two edge images. The image fusion process comprises three stages: discrete wavelet transform for image decomposition, a fusion rule for merging the coefficients, and the inverse transform for image synthesis. In the experiments, various types of metallic and non-metallic objects such as a knife, gel or liquid type beauty aids and a phone are detected by passive millimeter wave imaging. The registration and fusion process can visualize the meaningful information from two different types of sensors.