• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.397-403
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• 2015

In this paper, a method of ISAR geometric calibration is represented by using impulse-radio UWB radar. The ir-UWB is good for using a signal processing in time domain, so, it does not occur a multi-path or coupling problem. If a signal that between antennas and target is assumed a plane wave, a center of rotation in ISAR geometry model can be estimated by using point target. Before image is reconstructed with sinogram, the center of rotation can be calculated by using least square fitting. This method can be obtained a more contrast image, and a maximum value of entropy of image. The method, that estimates a center of rotation in received data, will be used a initial setup of instruments or a periodic compensation to reconstruct image. It would be useful in medical, security and surveillance imaging equipments that have a fixed geometry.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1247-1254
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• 2003

Currently. the north american symptomatic carotid endarterectomy trial, european carotid surgery trial, and common carotid method are used to measure the carotid stenosis for determining candidate for carotid endarterectomy using the projection angiography from different modalities such as digital subtraction angiography. rotational angiography, computed tomography angiography and magnetic resonance angiography. A new computerized carotid stenosis measuring system was developed using MR angiography axial image to overcome the drawbacks of conventional carotid stenosis measuring methods, to reduce the variability of inter-observer and intra-observer. The gray-level thresholding is one of the most popular and efficient method for image segmentation. We segmented the carotid artery and lumen from three-dimensional time-of-flight MRA axial image using gray-level thresholding technique. Using the measured intima-media thickness value of common carotid artery for each cases, we separated carotid artery wall from the segmented carotid artery region. After that, the regions of segmented carotid without artery wall were divided into region of blood flow and plaque. The calculation of carotid stenosis degree was performed as the following; carotid stenosis grading is(area measure of plaque/area measure of blood flow region and plaque) * 100%.

• Archives of Plastic Surgery
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• v.50 no.4
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• pp.340-347
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• 2023

Background Though in facial plastic surgery, the ideal nasal characteristics are defined by average European-American facial features known as neoclassical cannons, many ethnicities do not perceive these characteristics as suitable. Methods To investigate the preferences for nasofrontal angle, nasolabial angle, dorsal height, alar width, and nasal tip projection, manipulated pictures of one male and one female model were shown to 203 volunteer patients from a tertiary university hospital's facial plastic clinic. Results The most aesthetically preferred nasofrontal angles were 137.64 ± 4.20 degrees for males and 133.55 ± 4.53 degrees for females. Acute nasofrontal angles were more desirable in participants aged 25 to 44. The most preferred nasolabial angles were 107.56 ± 5.20 degrees and 98.92 ± 4.88 degrees, respectively. Volunteers aged 19 to 24 preferred more acute male nasolabial angles. A straight dorsum was the most desirable in both genders (0.03 ± 0.78 and 0.26 ± 0.75 mm, respectively). The ideal male and female alar widths were -0.51 ± 2.26 and -1.09 ± 2.18 mm, respectively. More 45- to 64-year-old volunteers preferred alar widths equal to intercanthal distance. The ideal female and male tip projections were 0.57 ± 0.01 and 0.56 ± 0.01, respectively. Conclusion Results indicate that the general Iranian patients prefer thinner female noses with wider nasofrontal angles for both genders. However, the ideal nasolabial angles, dorsal heights, and tip projections were consistent with the neoclassical cannons. Besides ethnic differences, the trend of nasal beauty is also affected by gender, age, and prior history of aesthetic surgery.

• Journal of Biomedical Engineering Research
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• v.40 no.3
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• pp.105-115
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• 2019

Brain tumor surgery may be difficult, but it is also incredibly important. The technological improvements for traditional brain tumor surgeries have always been a focus to improve the precision of surgery and release the potential of the technology in this important area of the body. The need for precision during brain tumor surgery has led to an increase in Robotic-assisted surgeries (RAS). One of the challenges to the widespread acceptance of RAS in the neurosurgery is to recognize invisible tumor accurately. Therefore, it is important to detect brain tumor size and location because surgeon tries to remove as much tumor as possible. In this paper, we proposed brain tumor detection procedures for MRI (Magnetic Resonance Imaging) system. A method of automatic brain tumor detection is needed to accurately target the location of the lesion during brain tumor surgery and to report the location and size of the lesion. In the qualitative assessment, the proposed method showed better results than those obtained with other brain tumor detection methods. Comparisons among all assessment criteria indicated that the proposed method was significantly superior to the threshold method with respect to all assessment criteria. The proposed method was effective for detecting brain tumor.

• Journal of the Microelectronics and Packaging Society
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• v.22 no.2
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• pp.11-19
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• 2015

Since CMOS device scaling has stalled, three-dimensional (3-D) integration allows extending Moore's law to ever high density, higher functionality, higher performance, and more diversed materials and devices to be integrated with lower cost. 3-D integration has many benefits such as increased multi-functionality, increased performance, increased data bandwidth, reduced power, small form factor, reduced packaging volume, because it vertically stacks multiple materials, technologies, and functional components such as processor, memory, sensors, logic, analog, and power ICs into one stacked chip. Anticipated applications start with memory, handheld devices, and high-performance computers and especially extend to multifunctional convengence systems such as cloud networking for internet of things, exascale computing for big data server, electrical vehicle system for future automotive, radioactivity safety system, energy harvesting system and, wireless implantable medical system by flexible heterogeneous integrations involving CMOS, MEMS, sensors and photonic circuits. However, heterogeneous integration of different functional devices has many technical challenges owing to various types of size, thickness, and substrate of different functional devices, because they were fabricated by different technologies. This paper describes new 3-D heterogeneous integration technologies of chip self-assembling stacking and 3-D heterogeneous opto-electronics integration, backside TSV fabrication developed by Tohoku University for multifunctional convergence systems. The paper introduce a high speed sensing, highly parallel processing image sensor system comprising a 3-D stacked image sensor with extremely fast signal sensing and processing speed and a 3-D stacked microprocessor with a self-test and self-repair function for autonomous driving assist fabricated by 3-D heterogeneous integration technologies.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.28-34
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• 2018

This paper is composed of a passenger management system using a temperature sensing module, a PIR sensor module for detecting movement inside a room, and a smart breath sensing module for determining a sleeping state. An embedded sensor module and a communication system integrated the sensing part and the algorithm driving part. As the aging society is accelerating and becoming more upgraded, the social cost of Silver Care increases, and in order to protect privacy, it is necessary to reduce costs by developing efficient smart silver care devices. The proposed non - image human body detection IOT sensor system is implemented by hardware and software and has superior performance compared with conventional image monitoring method.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.212-221
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• 2008

The total hip replacement (THR) has been used as the most effective way to restore the function of damaged hip joint. However, various factors have caused some side effects after the THR. Unfortunately, the success of the THR have been decided only by the proficiency of surgeons so far. Hence, It is necessary to find the way to minimize the side effect caused by those factors. The purpose of this study was to suggest the definite data, which can be used to design and choose the optimal hip implant. Using finite element analysis (FEA), the biomechanical condition of bone cement was evaluated. Stress patterns were analyzed in three conditions: cement mantle, procimal femur and stem-cement contact surface. Additionally, micro-motion was analyzed in the stem-cement contact surface. The 3-D femur model was reconstructed from 2-D computerized tomography (CT) images. Raw CT images were preprocessed by image processing technique (i.e. edge detection). In this study, automated edge detection system was created by MATLAB coding for effective and rapid image processing. The 3-D femur model was reconstructed based on anatomical parameters. The stem shape was designed using that parameters. The analysis of the finite element models was performed with the variation of parameters. The biomechanical influence of each parameter was analyzed and derived optimal parameters. Moreover, the results of FE A using commercial stem model (Zimmer's V erSys) were similar to the results of stem model that was used in this study. Through the study, the improved designs and optimal factors for clinical application were suggested. We expect that the results can suggest solutions to minimize various side effects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1310-1316
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• 2021

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.19-28
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• 2021

Esophagogastroduodenoscopy is a method commonly used for early diagnosis of upper gastrointestinal lesions. However, 10-20 percent of the gastric lesions are reported to be missed, due to human error. And countries including the US, the UK, and Japan, the World Endoscopy Organization (WEO) suggested guidelines about essential gastrointestinal parts to take pictures of so that all gastric lesions are observed. In this paper, we propose deep learning techniques for classification of anatomical sites, aiming for the system that informs practitioners whether they successfully did the gastroscopy without blind spots. The proposed model uses pre-processing modules and data augmentation techniques suitable for gastroscopy images. Not only does the experiment result with a maximum F1 score of 99.6%, but it also shows a error rate of less than 4% based on the actual data. Given the performance results, we found the model to be explainable with the potential to be utilized in the clinical area.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.61-67
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• 2021

In this paper, we propose a method of extracting and recognizing related information for research from images of the unstructured pulmonary function test papers using character detection and recognition techniques. Also, we develop a post-processing method to reduce the character recognition error rate. The proposed structuring method uses a character detection model for the pulmonary function test paper images to detect all characters in the test paper and passes the detected character image through the character recognition model to obtain a string. The obtained string is reviewed for validity using string matching and structuring is completed. We confirm that our proposed structuring system is a more efficient and stable method than the structuring method through manual work of professionals because our system's error rate is within about 1% and the processing speed per pulmonary function test paper is within 2 seconds.