• Korean Journal of Radiology
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• v.23 no.7
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• pp.752-762
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• 2022

Objective: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods: Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results: The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001). Conclusion: For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.377-382
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• 1994

In the conventional Fourier imaging method in MRI (Magnetic Resonance Imaging), intramotion such as pulsatile flow makes zipper-like artifact along the phase encoding direction. On the other hand, line-integral projection reconstruction (LPR) method has advantages such as imaging of short T2, object and reduction of the flow artifact by elimination of the flow-induced phase fluctuation. The LPR, however, necessarily requires time consuming filtering and back-projection processes, so that the reconstruction takes long time. To overcome the long reconstruction time of the LPR and to obtain the flow artifact reduction effect, we adopted phase corrected concentric square raster sampling (CSRS) method and improved its imaging performance. The CSRS is a fast reconstruction method which has the same properties with the LPR. In this paper, we proposed a new method of flow artifact reduction using the CSRS method. Through computer simulations and experiments, we verified that the proposed method can eliminate phase fluctuations, thereby reducing the flow artifact and re- markably shorten the reconstruction time which required long time in the LPR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.784-787
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• 2006

In this paper, we propose a method for nonlinear grapheme segmentation in Korean printed character type classification. The characters are subdivided into six types based on character type information. The feature vector is consist of mesh features, vertical projection features and horizontal projection features which are extracted from gray-level images. We classify characters into 6 types using Back propagation. Character segmentation regions are determined based on character type information. Then, an optimal nonlinear grapheme segmentation path is found using multi-stage graph search algorithm. As the result, a proposed methodology is proper to classify character type and to find nonlinear char segmentation paths.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.173-181
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• 2004

In this paper, we propose a system for automatic moving object detection and tracking in sequence images acquired from a moving camera. The proposed algorithm consists of moving object detection and its tracking. Moving object can be detected by integration of BBME and DD method We segment the detected object using histogram back projection, match it using histogram intersection, extract and track it using XY-projection. Computer simulation results have shown that the proposed algorithm is reliable and can successfully detect and track a moving object on image sequences obtained by a moving camera.

• Progress in Medical Physics
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• v.32 no.2
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• pp.50-58
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• 2021

Purpose: In this study, we investigated the relationship between the noise characteristics and the number of projected images in tomosynthesis using a digital phantom. Methods: The digital phantom consisted of a columnar phantom in the center of the image and a spherical phantom with a diameter of 80 pixels. A virtual scan was performed, and 128 projected images (Tomo_w/o) of the phantoms were obtained. The image noise according to the Poisson distribution was added to the projected images (Tomo_×1). Furthermore, another projected image with additional noise was prepared (Tomo_×1/2). For each dataset, we created datasets with 64 (half) and 32 (quarter) projections by removing the even-numbered images twice from the 128 (fully) projected images. Tomosynthesis images were reconstructed by filtered back projection (FBP). The modulation transfer function (MTF) was estimated using the sphere method, and the noise power spectrum (NPS) was estimated using the two-dimensional Fourier transform method. Results: The MTFs did not change between datasets, and the NPSs improved as the number of projected images increased. The noise characteristics of the Tomo_×1_half images were the same as those of the Tomo_×1/2_full. Conclusions: To achieve a reduction in the patient dose in tomosynthesis acquisition, we recommend reducing the number of projected images rather than reducing the dose per projection.

• Korean Journal of Optics and Photonics
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• v.26 no.4
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• pp.226-232
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• 2015

A double-layer LED array together with an illumination optical system is proposed as a possible light source for LC projection display systems for large screens, up to $8m{\times}6m$ (400 inches diagonal). The heat dissipation problem of the LED array is solved by arranging the LEDs in double layers, and thermal analysis shows its effectiveness. The light from the LEDs in the back layer can be transmitted through the front layer without significant loss by arranging the LEDs in non-overlapping positions in the two layers and inserting suitable microlenses between the two layers and holes in the first layer. Together with the double-layer LEDs, an illumination optical system is designed to illuminate liquid crystal panels with good uniformity and appropriate matching with the projection optics.

• Journal of the Korean Wood Science and Technology
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• v.41 no.5
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• pp.385-391
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• 2013

X-ray computed tomography is a very powerful nondestructive technique in safety inspection of historic timber building. But, in field, various testing condition makes it difficult to carry out X-ray CT testing. Limited size in X-ray digital detector is one of the problems. In this study, a pitch pine disk with two holes was used to know how imperfection in X-ray projection affects CT image resolution. Using various number of projections, CT image was reconstructed by filtered back projection method, and then it was investigated how many projection is required to identify the holes in different location. Two artificial holes could be differently detected according to their location in cross section of specimen. One hole in center part of specimen was identified using more than 9 radiographs, but the other one which located in outer part of cross section could not be detected until more than 36 projections were used. Even though there is data missing in outer part of cross section due to limited size of detector, the center part of CT image could be reconstructed well and the resolution of outer part became higher with increase of the number of projections. For field application, the number of projections for CT image reconstruction needs to be decided with consideration of another nondestructive testing and the location of interest.

• Journal of Navigation and Port Research
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• v.38 no.2
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• pp.185-191
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• 2014

With the 500th anniversary commemoration of Gerard Mercator's birth in 2012 now passed, there is the possibility that his name will fade back into obscurity. This would be both unfair and pitiful, because Gerard Mercator's name should be highly regarded as one of the principal contributors to navigational science and the promotion of marine safety. An accomplished cartographer, in 1569 Mercator published a remarkable 18-folio world map, depicting the then-known world in a new format with straight rhumb lines. While this distorted the size of land masses, particularly in higher latitudes, this new projection made navigation much easier for now all sailors had to do was to draw a straight line between two points to plot their course. Mercator clearly had this navigational benefit in mind, though his contemporaries did not immediately recognize its value. It wasn't until after Mercator's death, when Edward Wright (1599) and Henry Bond (1645) used and explained the new projection and demonstrated the use of straight rhumb lines in navigation that the Mercator projection became the standard for sea charts. Today, 450 years later of his death, electronic charts still rely on the projection Mercator invented and developed, confirming his position as a giant in the history of navigation. This paper introduces his life and work, detailing the importance of the 1569 world map and its contribution to navigational science and safety.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• Proceedings of the KSRS Conference
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• v.1
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• pp.508-511
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• 2006

Generally, stereo pair images are necessary for 3D viewing. In the absence of quality stereo-pair images, it is possible to synthesize a stereo-mate suitable for 3D viewing with a single image and a depth-map. In remote sensing, DEM is usually used as a depth-map. In this paper, LiDAR data was used instead of DEM to make a stereo pair from a single aerial photo. Each LiDAR point was assigned a brightness value from the original single image by registration of the image and LiDAR data. And then, imaginary exposure station and image plane were assumed. Finally, LiDAR points with already-assigned brightness values were back-projected to the imaginary plane for synthesis of a stereo-mate. The imaginary exposure station and image plane were determined to have only a horizontal shift from the original image's exposure station and plane. As a result, the stereo-mate synthesized in this paper fulfilled epipolar geometry and yielded easily-perceivable 3D viewing effect together with the original image. The 3D viewing effect was tested with anaglyph at the end.