• Korean Journal of Radiology
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• v.22 no.11
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• pp.1918-1928
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• 2021

Objective: With the recent development of various MRI-conditional cardiac implantable electronic devices (CIEDs), the accurate identification and characterization of CIEDs have become critical when performing MRI in patients with CIEDs. We aimed to develop and evaluate a deep learning-based algorithm (DLA) that performs the detection and characterization of parameters, including MRI safety, of CIEDs on chest radiograph (CR) in a single step and compare its performance with other related algorithms that were recently developed. Materials and Methods: We developed a DLA (X-ray CIED identification [XCID]) using 9912 CRs of 958 patients with 968 CIEDs comprising 26 model groups from 4 manufacturers obtained between 2014 and 2019 from one hospital. The performance of XCID was tested with an external dataset consisting of 2122 CRs obtained from a different hospital and compared with the performance of two other related algorithms recently reported, including PacemakerID (PID) and Pacemaker identification with neural networks (PPMnn). Results: The overall accuracies of XCID for the manufacturer classification, model group identification, and MRI safety characterization using the internal test dataset were 99.7% (992/995), 97.2% (967/995), and 98.9% (984/995), respectively. These were 95.8% (2033/2122), 85.4% (1813/2122), and 92.2% (1956/2122), respectively, with the external test dataset. In the comparative study, the accuracy for the manufacturer classification was 95.0% (152/160) for XCID and 91.3% for PPMnn (146/160), which was significantly higher than that for PID (80.0%,128/160; p < 0.001 for both). XCID demonstrated a higher accuracy (88.1%; 141/160) than PPMnn (80.0%; 128/160) in identifying model groups (p < 0.001). Conclusion: The remarkable and consistent performance of XCID suggests its applicability for detection, manufacturer and model identification, as well as MRI safety characterization of CIED on CRs. Further studies are warranted to guarantee the safe use of XCID in clinical practice.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.8
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• pp.52-59
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• 2007

In this paper, we analyzed and measured implant isolation characteristics for a 1.25 Gbps monolithic integrated hi-directional (M-BiDi) optoelectronic system-on-a-chip, which is a key component to constitute gigabit passive optical networks (PONs) for a fiber-to-the-home (FTTH). Also, we derived an equivalent circuit of the implant structure under various DC bias conditions. The 1.25 Gbps M-BiDi transmit-receive SoC consists of a laser diode with a monitor photodiode as a transmitter and a digital photodiode as a digital data receiver on the same InP wafer According to IEEE 802.3ah and ITU-T G.983.3 standards, a receiver sensitivity of the digital receiver has to satisfy under -24 dBm @ BER=10-12. Therefore, the electrical crosstalk levels have to maintain less than -86 dB from DC to 3 GHz. From analysed and measured results of the implant structure, the M-BiDi SoC with the implant area of 20 mm width and more than 200 mm distance between the laser diode and monitor photodiode, and between the monitor photodiode and digital photodiode, satisfies the electrical crosstalk level. These implant characteristics can be used for the design and fabrication of an optoelectronic SoC design, and expended to a mixed-mode SoC field.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.12
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• pp.6-13
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• 2009

For X-band phased array systems, a power amplifier, a 6-bit phase shifter, a 6-bit digital attenuator, and a SPDT transmit/receive (T/R) switch are fabricated and measured. All circuits are demonstrated by using CMOS 0.18 um technology. The power amplifier has 2-stage differential and cascade structures. It provides 1-dB gain-compressed output power ($P_{1dB}$) of 20 dBm and power-added-efficiency (PAE) of 19 % at 8-11 GHz frequencies. The 6-bit phase shifter utilizes embedded switched filter structure which consists of nMOS transistors as a switch and meandered microstrip lines for desired inductances. It has $360^{\circ}$ phase-control range and $5.6^{\circ}$ phase resolution. At 8-11 GHz frequencies, it has RMS phase and amplitude errors are below $5^{\circ}$ and 0.8 dB, and insertion loss of $-15.7\;{\pm}\;1,1\;dB$. The 6-bit digital attenuator is comprised of embedded switched Pi-and T-type attenuators resistive networks and nMOS switches and employes compensation circuits for low insertion phase variation. It has max. attenuation of 31.5 dB and 0.5 dB amplitude resolution. Its RMS amplitude and phase errors are below 0.4 dB and $2^{\circ}$ at 8-11 GHz frequencies, and insertion loss is $-10.5\;{\pm}\;0.8\;dB$. The SPDT T/R switch has series and shunt transistor pairs on transmit and receive path, and only one inductance to reduce chip area. It shows insertion loss of -1.5 dB, return loss below -15 dB, and isolation about -30 dB. The fabricated chip areas are $1.28\;mm^2$, $1.9mm^2$, $0.34\;mm^2$, $0.02mm^2$, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.648-658
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• 2003

As the usage of image/video contents increase, a security problem for the payed image data or the ones requiring confidentiality is raised. This paper proposed an image encryption methodology to hide the image information. The target data of it is the result from quantization in wavelet domain. This method encrypts only part of the image data rather than the whole data of the original image, in which three types of data selection methodologies were involved. First, by using the fact that the wavelet transform decomposes the original image into frequency sub-bands, only some of the frequency sub-bands were included in encryption to make the resulting image unrecognizable. In the data to represent each pixel, only MSBs were taken for encryption. Finally, pixels to be encrypted in a specific sub-band were selected randomly by using LFSR(Linear Feedback Shift Register). Part of the key for encryption was used for the seed value of LFSR and in selecting the parallel output bits of the LFSR for random selection so that the strength of encryption algorithm increased. The experiments have been performed with the proposed methods implemented in software for about 500 images, from which the result showed that only about 1/1000 amount of data to the original image can obtain the encryption effect not to recognize the original image. Consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. Also, in this paper, several encryption scheme according to the selection of the sub-bands and the number of bits from LFSR outputs for pixel selection have been proposed, and it has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.

• Journal of IKEEE
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• v.27 no.4
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• pp.464-471
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• 2023

In this paper, we propose a method to reduce age distortion in facial expression image generation using StyleGAN Encoder. The facial expression image generation process first creates a face image using StyleGAN Encoder, and changes the expression by applying the learned boundary to the latent vector using SVM. However, when learning the boundary of a smiling expression, age distortion occurs due to changes in facial expression. The smile boundary created in SVM learning for smiling expressions includes wrinkles caused by changes in facial expressions as learning elements, and it is determined that age characteristics were also learned. To solve this problem, the proposed method calculates the correlation coefficient between the smile boundary and the age boundary and uses this to introduce a method of adjusting the age boundary at the smile boundary in proportion to the correlation coefficient. To confirm the effectiveness of the proposed method, the results of an experiment using the FFHQ dataset, a publicly available standard face dataset, and measuring the FID score are as follows. In the smile image, compared to the existing method, the FID score of the smile image generated by the ground truth and the proposed method was improved by about 0.46. In addition, compared to the existing method in the smile image, the FID score of the image generated by StyleGAN Encoder and the smile image generated by the proposed method improved by about 1.031. In non-smile images, compared to the existing method, the FID score of the non-smile image generated by the ground truth and the method proposed in this paper was improved by about 2.25. In addition, compared to the existing method in non-smile images, it was confirmed that the FID score of the image generated by StyleGAN Encoder and the non-smile image generated by the proposed method improved by about 1.908. Meanwhile, as a result of estimating the age of each generated facial expression image and measuring the estimated age and MSE of the image generated with StyleGAN Encoder, compared to the existing method, the proposed method has an average age of about 1.5 in smile images and about 1.63 in non-smile images. Performance was improved, proving the effectiveness of the proposed method.