• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.21-29
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• 2007

In this paper, we present a method of detecting the boundary of the intima-media complex for automated measurement based on dynamic programming from carotid artery B-mode ultrasound images and then show the experimental results. We apply the dynamic programming for determining the optimal locations that a cost function is minimized. The cost function includes cost terms which are representing image features such as intensity, intensity gradient and geometrical continuity of the vessel interfaces. Moreover, we improve the boundary continuity by applying the B-spline to smooth the rough boundary due to noise such as speckle, dropout and weak edges. The proposed method has obtained more accurate reproducible results than conventional edge-detection by considering multiple image features and ensures efficient automated measurement by solving the problems of the inter- and intra-observer variability and its inefficiency due to manual measurement.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.2
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• pp.128-133
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• 2015

This paper describes the construction of a static 3D ultrasonography image by tracking the radiation beam position during the handy operation of a 1D array probe to enable point-of-care use. The theoretical model of the transformation from the translational and rotational information of the sensor mounted on the probe to the reference Cartesian coordinate system was given. The signal amplification and serial communication interface module was made using a commercially available sensor. A test phantom was also made using silicone putty in a donut shape. During the movement of the hand-held probe, B-mode movie and sensor signals were recorded. B-mode images were periodically selected from the movie, and the gray levels of the pixels for each image were converted to the gray levels of 3D voxels. 3D and 2D images of arbitrary cross-section of the B-mode type were also constructed from the voxel data, and agreed well with the shape of the test phantom.

• Journal of Advanced Engineering and Technology
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• v.11 no.4
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• pp.245-251
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• 2018

Terahertz waves (T-ray) was extensively studied for the NDE (nondestructive evaluation) of characterization of trailing edges for a use of turbines composed with composite materials. The used NDE system were consisted of both CW(Continuous wave) and TDS (Time domain spectroscopy). The FRP composites were utilized for two kinds of both trailing edges of wind energy (non-conducting polymeric composites) and carbon fiber composites with conducting properties. The signals of T-ray in the TDS (Time domain spectroscopy) mode resembles almost that of ultrasound waves; however, a terahertz pulse could not penetrate a material with conductivity unlike ultrasound. Also, a method was suggested to obtain the "n" in the materials, which is called the refractive index (n). The data of refractive index (n) could be solved for the trailing edges. The trailing edges were scanned for characterization and inspection. C-scan and B-scan images were obtained and best optimal NDE techniques were suggested for complicated geometry samples by terahertz radiation. Especially, it is found that the defect image of T-ray corresponded with defect locations for the trailing edges of wind mill.

• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.6-13
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• 2005

Individual clinical significance of each layer of CCA (common carotid artery) has not been well studied. We intended to measure the intima thickness (IT), media thickness (MT), and intima-media thickness (IMT) of CCA separately and tried to analyze the clinical significance. One hundred fifty one consecutive patients (mean age: $57{\pm}15$ years; 77 males, 74 females) underwent CCA scanning using high-resolution ultrasound. The images were off-line analyzed using B-mode ultrasound image processing, devised for individual measurement of IT and MT as well as IMT. The mean coefficients of variation of new method measuring IT, MT, and IMT separately were 0.16% for IMT and 0.21% for both IT and MT. The IT (p < 0.01), MT (p < 0.01) as well as IMT (p < 0.001) of patients with atherosclerotic disease were significantly thicker than that of the patients without atherosclerotic disease. Patients with hypertension showed significantly thicker IT (p < 0.01), MT (p < 0.001), and IMT (p < 0.001) than that of the patients without hypertension. However, only IT was thicker in patients with smoking (p<0.01) than that of the patients without smoking.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.66-71
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• 1998

High spatial resolution ultrasonic imaging is necessary in several fields of investigation, in order to permit greater precision of clinical diagnosis in the dermatology, ophthalmology etc. We present a B-mode scan system using sector scanning probe of 20MHz center frequency. This developed system allow the high resolution image of 250${\mu}m$ in lateral and 80${\mu}m$ in axial, which of display the size of a $5mm {\times} 5mm$ image with 20 frames/sec. We have shown the images of various structural elements of the human skin and of the nail. We have compared the skin images obtained for each of the different age and we have shown in a general with the age, the atrophy of the skin thickness and the appearance of the abnormal hypoechogene band under epidermis (named SENEB : Sub Epidermal Non Echogene Band).

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.77-84
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• 2007

The intima media thickness(IMT) of the carotid artery from B mode ultrasound images has recently been proposed as the most useful index of individual atherosclerosis and can be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by manually tracing interfaces between tissue layers. The drawbacks of this method are the inter and intra observer variability and its inefficiency. In this paper, we present a multiresolution snake method combined with the dynamic programming, which overcomes the various noises and sensitivity to initialization of conventional snake. First, an image pyramid is constructed using the Gaussian pyramid that maintains global edge information with smoothing in the images, and then the boundaries are automatically detected in the lowest resolution level by minimizing a cost function based on dynamic programming. The cost function includes cost terms which are representing image features and geometrical continuity of the vessel interfaces. Since the detected boundaries are selected as initial contour of the snake for the next level, this automated approach solves the problem of the initialization. Moreover, the proposed snake improves the problem of converging th the local minima by defining the external energy based on multiple image features. In this paper, our method has been validated by computing the correlation between manual and automatic measurements. This automated detection method has obtained more accurate and reproducible results than conventional edge detection by considering multiple image features.

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

• International Journal of Vascular Biomedical Engineering
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• v.4 no.2
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• pp.25-30
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• 2006

We intended to measure the IT, MT, and the IMT of carotid artery separately and tried to analyze the clinical significance. Two hundred and fifty consecutive patients (125 males, 125 females) underwent carotid artery scanning using high-resolution ultrasound. The images were off-line analyzed using B-mode ultrasound image processing, devised in our research. We measured the IT, MT, and IMT semi-automatically at the far wall of designated 1cm length of the right common carotid and calculated the average values over the 200 points. The IT (p < 0.05), MT (p < 0.05) as well as IMT (p < 0.01) of patients with atherosclerotic disease were significantly thicker than that of the patients without atherosclerotic disease. Patients with hypertension showed significantly thicker IT (p < 0.05), MT (p < 0.01), and IMT (p < 0.01) than that of the patients without hypertension. However, only IT was thicker in patients with smoking (p < 0.05) than that of the patients without smoking. Smoking was associated only with intima while hypertension was associated with the all three layer's thickness. This result suggests the atherosclerotic process can be different by cardiovascular risk factors.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.2
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• pp.112-119
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• 2015

Photoacoustic microscopy is capable of providing high-resolution molecular images, and its spatial resolution is typically determined by ultrasonic transducers used to receive the photoacoustic signals. Therefore, ultrasonic transducers for photoacoustic microscopy (PAM) should have a high operating frequency, broad bandwidth, and high signal-reception efficiency. Polyvinylidene fluoride (PVDF) is a suitable material. To take full advantage of this material, the selection of the backing material is crucial, as it influences the center frequency and bandwidth of the transducer. Therefore, we experimentally determined the most suitable backing material among EPO-TEK 301, E-Solder 3022, and RTV. For this, three PVDF high-frequency single-element transducers were fabricated with each backing material. The center frequency and -6 dB bandwidth of each transducer were ascertained by a pulse-echo test. The spatial resolution of each transducer was examined using wire-target images. The experimental results indicated that EPO-TEK 301 is the most suitable backing material for a PAM transducer. This material provides the highest signal magnitude and a reasonable bandwidth because a large portion of the energy propagates toward the front medium, and the PVDF resonates in the half-wave mode.

• Korean Journal of Radiology
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• v.20 no.5
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• pp.749-758
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• 2019

Objective: To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between malignant and benign masses on breast ultrasound (US). Materials and Methods: B-mode US images were prospectively obtained for 253 breast masses (173 benign, 80 malignant) in 226 consecutive patients. Breast mass US findings were retrospectively analyzed by deep learning-based CAD and four radiologists. In predicting malignancy, the CAD results were dichotomized (possibly benign vs. possibly malignant). The radiologists independently assessed Breast Imaging Reporting and Data System final assessments for two datasets (US images alone or with CAD). For each dataset, the radiologists' final assessments were classified as positive (category 4a or higher) and negative (category 3 or lower). The diagnostic performances of the radiologists for the two datasets (US alone vs. US with CAD) were compared Results: When the CAD results were added to the US images, the radiologists showed significant improvement in specificity (range of all radiologists for US alone vs. US with CAD: 72.8-92.5% vs. 82.1-93.1%; p < 0.001), accuracy (77.9-88.9% vs. 86.2-90.9%; p = 0.038), and positive predictive value (PPV) (60.2-83.3% vs. 70.4-85.2%; p = 0.001). However, there were no significant changes in sensitivity (81.3-88.8% vs. 86.3-95.0%; p = 0.120) and negative predictive value (91.4-93.5% vs. 92.9-97.3%; p = 0.259). Conclusion: Deep learning-based CAD could improve radiologists' diagnostic performance by increasing their specificity, accuracy, and PPV in differentiating between malignant and benign masses on breast US.