• 한국방사선학회논문지
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• 제10권6호
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• pp.451-456
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• 2016

방사선 검사로 환자의 병을 진단하기 위해서는 방사선 피폭이 따르게 된다. 최소한의 피폭으로 병변을 진단하는 일반촬영에 이중 엑스선 에너지 기법의 임상적용 가능성을 SNR 및 화질 점수화의 지표로 조사하였다. 이중 엑스선 에너지 기법은 검출기로 사용되는 두 개의 Image Plate 사이에 0.5 mm 두께의 Cu와 Al 필터를 추가함으로써 구현하였다. 한 번의 엑스선 조사로 획득된 두 IP 영상을 Subtraction 및 Enhance Contrast 기법을 적용하여 획득하였다. Enhance 영상은 첫 번째 IP에서 획득한 First 영상보다 SNR이 우수한 것으로 측정되었다. 이 일반촬영의 이중 엑스선 에너지 기법은 피폭선량을 줄이면서 영상의 품질을 높일 수 있는 방법으로 임상에서 매우 유용하게 적용될 수 있을 것이다.

• 로봇학회논문지
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• 제9권3호
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• pp.140-146
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• 2014

This paper introduces a dual-arm robot painter system which is capable of sketching a camera-captured image with short line segments. To express various curved edges in the image by combining line segments, we first apply edge detection algorithm to the entire image, split the edged image into small boxed pieces, and then apply Hough Transformation to each piece so that the edges inside the piece can be approximated with short line segments. To draw the picture within a reasonable time, we designed a simple dual-arm robot system and controlled both arms concurrently according to linear interpolation algorithm. From the experiments, we could verify that simple linear motions can describe various images effectively with a unique brush style.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2555-2575
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• 2017

This paper presents a dual exposure fusion method for image enhancement. Images taken with a short exposure time usually contain a sharp structure, but they are dark and are prone to be contaminated by noise. In contrast, long-exposure images are bright and noise-free, but usually suffer from blurring artifacts. Thus, we fuse the dual exposures to generate an enhanced image that is well-exposed, noise-free, and blur-free. To this end, we present a new scale-space patch-match method to find correspondences between the short and long exposures so that proper color components can be combined within a proposed dual non-local (DNL) means framework. We also present a residual filtering method that eliminates the structure component in the estimated noise image in order to obtain a sharper and further enhanced image. To this end, the entropy is utilized to determine the proper size of the filtering window. Experimental results show that our method generates ghost-free, noise-free, and blur-free enhanced images from the short and long exposure pairs for various dynamic scenes.

• JSTS:Journal of Semiconductor Technology and Science
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• 제12권4호
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• pp.388-396
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• 2012

In this paper, a $320{\times}240$ pixel, 80 frame/s CMOS image sensor with a low power dual correlated double sampling (CDS) scheme is presented. A novel 8-bit hold-and-go counter in each column is proposed to obtain 10-bit resolution. Furthermore, dual CDS and a configurable counter scheme are also discussed to realize efficient power reduction. With these techniques, the digital counter consumes at least 43% and at most 61% less power compared with the column-counters type, and the frame rate is approximately 40% faster than the double memory type due to a partial pipeline structure without additional memories. The prototype sensor was fabricated in a Samsung $0.13{\mu}m$ 1P4M CMOS process and used a 4T APS with a pixel pitch of $2.25{\mu}m$. The measured column fixed pattern noise (FPN) is 0.10 LSB.

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.293-302
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• 1989

A Dual Sensor Wiener Filter technique was used to improve the image quality of the scanning type digital radiographic system (resolution and SNR). In this method, two images were acquried simultaneously using two sensors with high and low resolution and SNR values. Using the cross Power spectrum between dual sensor outputs of the same chest radiographic image. we design a new type of Wiener Filter and implement it with fast algorithm. We compared the performance of this new dual sensor filter with conventional single sensor filters (Wiener Filter and Parametric Projec- tion Filter) . In simulation studies, it is shown that this new method has SNR improvement of 1-3 dB better than conventional filters.

• 한국정밀공학회지
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• 제24권2호
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• pp.86-94
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• 2007

In this paper, a dual stage servo mechanism has been developed for image tracking system to improve control performances such as small rise time, small overshoot, small settling time, small stabilization error etc. A secondary stage, a platform, actuated by a pair of electro-magnets is mounted on a conventional elevation gimbal. In this mechanism, the gimbal provides large range but slow motion and the platform provides small range but fast positioning. A sliding mode control is applied to the platform positioning to attain robust performances and stability in the presence of the disturbance related to dynamic coupling of the gimbal and the platform. Results from experiments illustrate that the suggested dual stage mechanism controlled by the sliding mode control is effective in improving responses and attenuating the disturbance response related with dynamic coupling.

• 한국산학기술학회논문지
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• 제11권9호
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• pp.3517-3523
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• 2010

본 논문은 이중 에너지 DR(Digital Radiography) 방식 중, 단일 조사 X-선(single shot X-ray exposure) 장치와 이중 모드 검출기 모듈 (Low Energy Detector & High Energy Detector)을 이용한 이중 X-선 이미징이 가능한 검출기 모듈에 관한 연구이다. 상용 BIS(baggage inspection system)에서 사용되고 있는 X-선 발생장치의 스펙트럼과 이중 모드 검출기에 대한 특징 및 방사선적 특성을 분석하여 새롭게 제안 할 검출기 모듈의 최적 설계 방향을 기술하고 상용화된 용화된 LED 및 HED 검출기와 새롭게 제안 한 검출기 모듈에 대해 전기적, 광학적, 방사선적 특성 실험을 실시하여, 새롭게 제안된 검출기 모듈이 BIS 용도로 사용 가능함을 증명하였다. 새롭게 제안 된 검출기 모듈이 적용된 BIS에 대해, 기본 특성 실험에 대한 X-선 영상을 획득하여 실험 및 분석을 실시하였다.

• Journal of Information Processing Systems
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• 제9권3호
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

• Korean Journal of Radiology
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• 제19권6호
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• pp.1031-1041
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• 2018

Objective: To compare image quality and radiation dose of high-pitch dual-source spiral cardiothoracic computed tomography (CT) between non-electrocardiography (ECG)-synchronized and prospectively ECG-triggered data acquisitions in young children with congenital heart disease. Materials and Methods: Eighty-six children (${\leq}3$ years) with congenital heart disease who underwent high-pitch dual-source spiral cardiothoracic CT were included in this retrospective study. They were divided into two groups (n = 43 for each; group 1 with non-ECG-synchronization and group 2 with prospective ECG triggering). Patient-related parameters, radiation dose, and image quality were compared between the two groups. Results: There were no significant differences in patient-related parameters including age, cross-sectional area, body density, and water-equivalent area between the two groups (p > 0.05). Regarding radiation dose parameters, only volume CT dose index values were significantly different between group 1 ($1.13{\pm}0.09mGy$) and group 2 ($1.07{\pm}0.12mGy$, p < 0.02). Among image quality parameters, significantly higher image noise ($3.8{\pm}0.7$ Hounsfield units [HU] vs. $3.3{\pm}0.6HU$, p < 0.001), significantly lower signal-to-noise ratio ($105.0{\pm}28.9$ vs. $134.1{\pm}44.4$, p = 0.001) and contrast-to-noise ratio ($84.5{\pm}27.2$ vs. $110.1{\pm}43.2$, p = 0.002), and significantly less diaphragm motion artifacts ($3.8{\pm}0.5$ vs. $3.7{\pm}0.4$, p < 0.04) were found in group 1 compared with group 2. Image quality grades of cardiac structures, coronary arteries, ascending aorta, pulmonary trunk, lung markings, and chest wall showed no significant difference between groups (p > 0.05). Conclusion: In high-pitch dual-source spiral pediatric cardiothoracic CT, additional ECG triggering does not substantially reduce motion artifacts in young children with congenital heart disease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.