• The Journal of the Acoustical Society of Korea
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• v.29 no.8
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• pp.504-508
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• 2010

In conventional diagnostic ultrasound strain imaging, when displaying strain image on a monitor, human visual characteristics are utilized such that hard regions are displayed as dark and soft regions are displayed as bright. Thus, hard regions representing tumor or cancer are displayed as dark, decreasing the contrast inside the lesion. Because the lesion area is stiff and thus displayed as dark, a method of inverting the image brightness and thereby increasing the contrast in the lesion for better diagnostic purposes is proposed wherein a postcompression signal is extended in the time domain by a factor corresponding to the reciprocal of the amount of the applied compression using a technique termed globally uniform stretching. Experiments were carried out to verify the proposed method on an ultrasound elasticity phantom with radio-frequency data acquired from a diagnostic ultrasound clinical scanner. It is found that the new method improves the contrast-to-noise ratio by a factor of up to about 1.8 compared to a conventional strain imaging method that employs a reversed gray color map without globally uniform stretching.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.991-997
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• 2009

Transmit beamforming is simple method to achieve the full diversity gain that is available in multiple antenna(MIMO) wireless systems. Unfortunately, the prior condition to achieve this gain requires perfect channel knowledge at both transmitter and receiver, which is impractical on account of limited feedback link. Therefore, for the practical system, codebook based feedback scheme is often employed, where the beamforming vector is selected from the codebook to maximize the output signal-to-noise ratio (SNR) at receiver, and the receiver only sends back the index of the best beamforming vector to the transmitter. In this paper we derive analytical expression of average bit error rate (BER) for the codebook based transmit beamforming MISO system over the feedback error channel. Using this analytical result, we present optimum codebook indexing scheme to improve the performance of this system. From some selected numerical examples we show that our proposed codebook indexing scheme can provide nonnegligible performance improvements in terms of average BER over the severe feedback error channel.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.147-159
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• 2013

In medical visualization, volume visualization is widely used. Applying 3D images to diagnose requires high resolution and accurately implement visualization techniques are being researched accordingly. However, when a three-dimensional image volume visualization is implemented using volume data, aliasing will occur since using discrete data. Supersampling method, getting lots of samples, is used to reduce artifacts. One of the supersampling methods is Catmull-rom spline. This method calculates accurate interpolation value because it is easy to compute and pass through control points. But, Catmull-rom spline method occurs overshoot or undershoot in large gradient of pixel values. So, interpolated values are different from original signal. In this paper, we propose an adaptive adjusting weights interpolation method using Gaussian function. Proposed method shows that overshoot is reduced on the point has a large gradient and PSNR is higher than other interpolated image results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8A
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• pp.610-617
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• 2009

This paper proposes a cross-layer design combining adaptive modulation and coding (AMC) with truncated hybrid automatic repeat request (HARQ) for wireless multicast transmission, in order to increase the spectral efficiency while meeting the target quality-of-service (QoS). In the design, we provide the selection criterion of AMC so as to satisfy the target packet error rate (PER) of all users when the multicast data is received through the common channel and the number of retransmission is limited by the delay constraint of the service. The analytically derived results show that the cross-layer design using HARQ provides a better spectral efficiency than the AMC without HARQ by allowing retransmission and code combining. It is also observed that the design for multicast outperforms that for unicast in the mid to high signal-to-noise ratio region.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.506-514
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• 2016

In this study, HEVC over DVB-T2 systems with a bandwidth of 6 MHz is considered, particularly for the terrestrial 4K-UHDTV broadcasting service in the Republic of Korea. The threshold of visibility carrier-to-noise power ratio (ToV C/N) and the receiver minimum required input level (sensitivity) for satisfying the subjective picture failure (SPF) condition are measured in the laboratory. It is observed, for transmitting 26.37 Mbps data stream correctly, that ToV C/N is 18.8 dB on average, and the receiver sensitivity is varied from minimum -84.2 dBm to maximum -80.0 dBm. Based on the results, the receiver noise floor is calculated by -100 dBm on average.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.938-946
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• 2012

Interference alignment (IA) is a data transmission technique that achieves the maximum degrees-of-freedom (DoF) in the multiuser interference channel for high signal-to-noise ratios (SNRs). However, most prior works on IA are based on the unrealistic assumption that perfect and global channel-state information (CSI) is available at all transmitters and receivers. In this paper, we propose the efficient design of feedback framework for IA that substantially suppresses the feedback overhead. While the feedback overhead in the conventional IA quadratically increases with K, the proposed feedback scheme supports the sequential exchange of computed IA precoders between transmitters and receivers and reduces the feedback overhead that linearly scales with K. Moreover, we analyze the residual interference due to the quantization error in limited feedback and propose the ordered IA algorithm that selects IA pair to minimize the sum residual interference in given channel realizations.

• Journal of the Korean Society of Radiology
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• v.9 no.2
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• pp.121-124
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• 2015

Digital Mammography is very important for the early diagnosis of breast cancer. but excessive radiation dose to the patient may increase the probability of occurrence of breast cancer. absorbed dose rate and signal, noise, and contrast in accordance with the change of the filter, and analyzed the signal-to-noise ratio. absorbed dose rate GE Equipment is higher than that of Siemens and Hologic. using the material of Mo / Mo was lower than the other target-filter combination. SNR of Siemens equipment is high and measured high when Mo / Mo selected, the other two devices was measured high when Mo / Rh selected. when you choose a target-filter combination our results will be a good indicator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7A
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• pp.562-567
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• 2009

In this paper, two-hop beamforming relay system, with source, relay, and destination nodes, is considered and the transmit- and receive-beamforming vectors and the relay processing matrix are designed for minimizing a mean square error (MMSE) between the transmit and receive signals. Here, to reduce the transmit power of the source or the relay, two local inequality constraints are involved with MMSE problem. By adopting the Lagrange method, closed formed Karush-Kuhn-Tucker (KKT) conditions (equalities) are derived and an iterative algorithm is developed to solve the entangled KKT equalities. Due to the inequality power constraints, the source or the relay can reduce its transmit power when the received signal-to-noise ratios (SNRs) of the first- and the second-hop are different. Meanwhile, the destination can achieve almost identical bit-error-rate performance compared to an optimal beamforming system maximizing the received SNR. This claim is supported by a computer simulation.

• Korean Journal of Optics and Photonics
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• v.10 no.4
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• pp.283-288
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• 1999

We investigated the characteristics of surface roughness evaluation using phase-measuring interferometer for a few ten $\AA$ and sub $\AA$-rough substrates. The influence of phase averaging and intensity averaging on the roughness measurement by phase measuring interferometer was investigated and the optimal number of phase and intensity averaging for the least measurement error was searched. For a few ten $\AA$-rough sample, roughness value did not depend so much on the data averaging. Whereas, measurement error for sub $\AA$-rough sample was significantly improved as the number of phase and intensity averaging increased. At the phase averaging of 30 and the intensity averaging of 20, roughness value that measurement error was minimized was obtained, and it was in good agreement with that by optical heterodyne interferometer. Roughness measurement at the optimal data averaging showed also good repeatability error less than 0.01$\AA$.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.709-715
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• 2023

In this study, the performance evaluation of image quality for noise reduction was implemented using the U-net deep learning architecture in computed tomography (CT) images. In order to generate input data, the Gaussian noise was applied to ground truth (GT) data, and datasets were consisted of 8:1:1 ratio of train, validation, and test sets among 1300 CT images. The Adagrad, Adam, and AdamW were used as optimizer function, and 10, 50 and 100 times for number of epochs were applied. In addition, learning rates of 0.01, 0.001, and 0.0001 were applied using the U-net deep learning model to compare the output image quality. To analyze the quantitative values, the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. Based on the results, deep learning model was useful for noise reduction. We suggested that optimized hyper parameters for noise reduction in CT images were AdamW optimizer function, 100 times number of epochs and 0.0001 learning rates.