• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.911-920
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• 2018

In this study, we performed a study to track the angle between the guided weapon and the target by using the strap-down image seeker, and constructed a test bed that can simulate it visually. This paper describes a method to maintain high-performance feature distribution in the implementation of sparse feature tracking algorithm such as Lucas Kanade's optical flow algorithm for target tracking using image information. We have extended the feature tracking problem to the concept of feature management. To realize this, we constructed visual environment using Unity3D engine and developed image processing simulation using OpenCV. For the co-simulation, dynamic system modeling was performed with Matlab Simulink, the visual environment using Unity3D was constructed, and computer vision work using OpenCV was performed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.1-14
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• 2000

The rosette-scan seeker, mounted on the infrared guided missile, is a device that tracks the target It can acquire the 2D image of the target by scanning a space about target in rosette pattern with a single detector Since the detected image is changed according to the position of the object in the field of view and the number of the object is not fixed, the unsupervised methods are employed in clustering it The conventional ISODATA method clusters the objects by using the distance between the seed points and pixels So, the clustering result varies in accordance with the shape of the object or the values of the merging and splitting parameters In this paper, we propose an Array Linkage Clustering Algorithm (ALCA) as a new clustering algorithm improving the conventional method The ALCA has no need for the initial seed points and the merging and splitting parameters since it clusters the object using the connectivity of the array number of the memory stored the pixel Therefore, the ALCA can cluster the object regardless of its shape With the clustering results using the conventional method and the proposed one, we confirm that our method is better than the conventional one in terms of the clustering performance We simulate the rosette scanning infrared seeker (RSIS) using the proposed ALCA as an infrared counter countermeasure The simulation results show that the RSIS using our method is better than the conventional one in terms of the tracking performance.

• Progress in Medical Physics
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• v.25 no.3
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• pp.143-150
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• 2014

In general radiotherapy, mega-voltage (MV) x-ray images are widely used as the unique method to verify radio-therapeutic fields. But, the image quality of MV images is much lower than that of kilo-voltage x-ray images due to scatter interactions. Since 1990s, studies for the scatter correction have performed with digital-based MV imaging systems. In this study, a novel method for the scatter correction is suggested using scatter to primary ratio (SPR), instead of conventional methods such as digital image processing or scatter kernel calculations. We measured two MV images with and without a solid water phantom describing a patient body with given imaging conditions, and calculated un-attenuated ratios. Then, we obtained SPR distributions for the scatter correction. For experimental validation, a line-pair (LP) phantom using several Al bars and a clinical pelvis MV image was used. As the result, scatter signals of the LP phantom image were successfully reduced so that original density distribution of the phantom was restored. Moreover, image contrast values increased after SPR correction at all ROIs of the clinical image. The mean value of increases was 48%. The SPR correction method suggested in this study has high reliability because it is based on actually measured data. Also, this method can be easily adopted in clinics without additional cost. We expected that the SPR correction can be an effective method to improve the quality of MV image guided radiotherapy.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.1
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• pp.7-18
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• 2017

Purpose: A QA Set was established to verify the movement accuracy of image-guided 6DoF Couch and to evaluate its usefulness. Materials and Methods: Two sets of linear accelerators equipped with 6DoF Couch and CBCT were used. Using the established QA Set, each CBCT image was obtained over 15 times through the Penta-Guide Phantom installed with off-set shift values along six translational (Translation; TX, TY, TZ) and rotational (Rotation, Pitch; RX, Roll; RY, Yaw; RZ) directions. Using this method, we compared the reference image and the registration image, and we analyzed the error calculated by measuring the positional accuracy of the modified 6DoF Couch. Results: The Air Cavity corresponding to the Pixel of the reference image and the registration image were all contained between 30 and 66, and the revealing high registration accuracy. Error between the modified off-set value of 6DoF Couch and the measured value along translational directions were $0.25{\pm}0.18mm$ in the TX direction, $0.25{\pm}0.25mm$ in the TY direction, and $0.36{\pm}0.2mm$ in the TZ direction. Misalignments along the rotational axis were $0.18{\pm}0.08^{\circ}$ in the RX direction, $0.26{\pm}0.09^{\circ}$ in the RY direction, and $0.11{\pm}0.08^{\circ}$ in the RZ direction, it was corrected precisely for any value. Conclusion: Using the YCC QA Set, we were able to verify the error of 6DoF Couch along both the translational and rotational directions in a very simple method. This system would be useful in performing Daily IGRT QA of 6DoF Couch.

• Journal of KIISE
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• v.43 no.3
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• pp.353-361
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• 2016

During image-guided radiation treatment of lung cancer patients, it is necessary to track the tumor motion because it can change during treatment as a consequence of respiratory motion and cardiac motion. In this paper, we propose a method for tracking the motion of the lung tumors based on the three-dimensional image information from planning 4D MDCT and treatment 4D CBCT images. First, to effectively track the tumor motion during treatment, the global motion of the tumor is estimated based on a tumor-specific motion model obtained from planning 4D MDCT images. Second, to increase the accuracy of the tumor motion tracking, the local motion of the tumor is estimated based on the structural information of the tumor from 4D CBCT images. To evaluate the performance of the proposed method, we estimated the tracking results of proposed method using digital phantom. The results show that the tumor localization error of local motion estimation is reduced by 45% as compared with that of global motion estimation.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.87-95
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• 2008

Ladar (Laser Detection And Ranging, Lidar) is a sensor to acquire precise distances to the surfaces of target region using laser signals, which can be suitably applied to ATD (Automatic Target Detection) for guided missiles or aerial vehicles recently. It provides a range image in which each measured distance is expressed as the brightness of the corresponding pixel. Since the precise 3D models can be generated from the Ladar range image, more robust identification and recognition of the targets can be possible. If we simulate the data of Ladar sensor, we can efficiently use this simulator to design and develop Ladar sensors and systems and to develop the data processing algorithm. The purposes of this study are thus to simulate the signals of a Ladar sensor based on linear frequency modulation and to create range images from the simulated Ladar signals. We first simulated the laser signals of a Ladar using FM chirp modulator and then computed the distances from the sensor to a target using the FFT process of the simulated signals. Finally, we created the range image using the distances set.

• Tuberculosis and Respiratory Diseases
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• v.76 no.2
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• pp.88-92
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• 2014

We hereby report a case on bronchogenic cyst which is initially non-infected, then becomes infected after bronchoscopic ultrasound (US)-guided transesophageal fine-needle aspiration (FNA). The non-infected bronchogenic cyst appears to be filled with relatively echogenic materials on US, and the aspirate is a whitish jelly-like fluid. Upon contrast-enhanced MRI of the infected bronchogenic cyst, a T1-weighted image shows low signal intensity and a T2-weighted image shows high signal intensity, with no enhancements of the cyst contents, but enhancements of the thickened cystic wall. The patient then undergo video-assisted thoracic surgery 14 days after the FNA. The cystic mass is known to be completely removed, and the aspirate is yellowish and purulent. To understand the image findings that pertain to the gross appearance of the cyst contents will help to diagnose bronchogenic cysts in the future.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.6
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• pp.438-444
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• 2021

Objectives: Loss of the interdental papilla is multi-factorial and creates a multitude of problems. Autogenous connective tissue/biomaterial-based regeneration has been attempted for decades to reconstitute the black space created due to the loss of papilla. The aim of this present study was to regenerate papillary recession defects using an amnion-chorion membrane (ACM) allograft and to evaluate the clinical outcome up to six months postoperatively. Materials and Methods: Twenty patients with 25 Nordland and Tarnow's Class I/II interdental papillary recession defects were treated with ACM and coronal advancement of the gingivo-papillary unit via a semilunar incision on the labial aspect followed by a sulcular incision in the area of interest. A photographic image analysis was carried out using the GNU Image Manipulation software program from the baseline to three and six months postoperatively. The black triangle height (BTH) and the black triangle width (BTW) were calculated using the pixel size and were then converted into millimeters. The mean and standard deviation values were determined at baseline and then again at three and six months postoperatively. The probability values (P<0.05 and P≤0.01) were considered statistically significant and highly significant, respectively. An analysis of variance and post hoc Bonferroni test were carried out to compare the mean values. Results: Our evaluation of the BTH and BTW showed a statistically and highly significant difference from the baseline until both three and six months postoperatively (P=0.01). A post hoc Bonferroni test disclosed a statistically significant variance from the baseline until three and six months postoperatively (P<0.05) and a non-significant difference from three to six months after the procedure (P≥0.05). Conclusion: An ACM allograft in conjunction with a coronally advanced flap could be a suitable minimally invasive alternative for papillary regeneration.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.205-208
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• 2022

Multi-exposure high dynamic range (HDR) image reconstruction, the task of reconstructing an HDR image from multiple low dynamic range (LDR) images in a dynamic scene, often produces ghosting artifacts caused by camera motion and moving objects and also cannot deal with washed-out regions due to over or under-exposures. While there has been many deep-learning-based methods with motion estimation to alleviate these problems, they still have limitations for severely moving scenes. They also require large parameter counts, especially in the case of state-of-the-art methods that employ attention modules. To address these issues, we propose a frequency domain approach based on the idea that the transform domain coefficients inherently involve the global information from whole image pixels to cope with large motions. Specifically we adopt Residual Fast Fourier Transform (RFFT) blocks, which allows for global interactions of pixels. Moreover, we also employ Depthwise Overparametrized convolution (DO-conv) blocks, a convolution in which each input channel is convolved with its own 2D kernel, for faster convergence and performance gains. We call this LFFNet (Lightweight Frequency Fusion Network), and experiments on the benchmarks show reduced ghosting artifacts and improved performance up to 0.6dB tonemapped PSNR compared to recent state-of-the-art methods. Our architecture also requires fewer parameters and converges faster in training.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.713-720
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• 2007

In image-guided surgery, automatic bone segmentation of Computed Tomography (CT) images is an important but challenging step. Previous attempts include intensity-, edge-, region-, and deformable curve-based approaches [1], but none claims fully satisfactory performance. Although active contour (AC) techniques possess many excellent characteristics, their applications in CT image segmentation have not worthily exploited yet. In this study, we have evaluated the automaticity and performance of the model of Chan-Vese Multiphase AC Without Edges towards knee bone segmentation from CT images. This model is suitable because it is initialization-insensitive and topology-adaptive. Its segmentation results have been qualitatively compared with those from four other widely used AC models: namely Gradient Vector Flow (GVF) AC, Geometric AC, Geodesic AC, and GVF Fast Geometric AC. To quantitatively evaluate its performance, the results from a commercial software and a medical expert have been used. The evaluation results show that the Chan-Vese model provides superior performance with least user interaction, proving its suitability for automatic bone segmentation from CT images.