• Korean Journal of Digital Imaging in Medicine
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• v.12 no.2
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• pp.81-87
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• 2010

The setting parameters of ultrasound scanner give influences to change of image. Sonographers have used a Matlab program to make Low Contrast Sensitivity(LCS) value and compared original images in order to evaluate the use of the supersonic diagnosis machinery. We confirmed the change of image in Grayscale values using Photoshop program. Experiment equipment of our research used A Medison Accuvix V10, A Multi-Tissue Ultrasound Phantom(040 GSE) of CHRIS Company, A Adobe Photoshop CS4 Program, A Convex Probe, A USB memory stick, A Probe Fixation Equipment. The method used Gain, Dynamic Range(DR) of the setting parameters of ultrasound scanner and researched Gain and DR was set to 10 dB. We changed the different settings to see the changes of images using Grayscale values of a Photoshop program about tissue images of a phantom. This study evaluated DR and Gain whether it is an image controller to get the optimum contrast to produce an image to see the how effect on the images. We did not use Gateway in supersonic diagnosis machinery. We can easily open to open the files through Photoshop program before we get Digital Imaging and Communications in Medicine(DICOM) files use USB memory stick in supersonic diagnosis machinery. When we diagnosed the lesion of the patient with ultrasound, the contrast and the Gray scale value of image are very important. In this research, we determined the optimum setting parameters that provided useful information to diagnose disease and evaluated the change of improved images.

• PNF and Movement
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• v.17 no.2
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• pp.329-337
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• 2019

Purpose: Ultrasound imaging is commonly used to measure the pennation angle of human skeletal muscles in vivo. However, manual assessment of the pennation angle using ultrasound images is subjective and time-consuming and requires a high level of examiner skill. The architectural analysis of human skeletal muscles is thus challenging. Automated approaches using image processing techniques are therefore required to estimate the pennation angle in ultrasound images. The purpose of this study was thus to assess the intra-tester and inter-tester reliability and validity of the pennation angle using an automatic measurement program. Methods: Twenty-two healthy young adults (mean age = 22.55 years) with no medical history of neurological or musculoskeletal disorders voluntarily participated in this study. Ultrasound imaging was used to measure the pennation angle of the gastrocnemius muscle at rest. One examiner acquired images from all the participants. The intra-tester and inter-tester reliability were evaluated using the intraclass correlation coefficient (ICC) to estimate reliability. Validity was measured using Pearson's correlation coefficient. Results: The intra-rater reliability was excellent for the automatic pennation angle measuring program and the manual pennation angle assessment method (ICC>0.95). The inter-rater reliability was also excellent for both methods (ICC>0.93). All the correlation coefficients for the automatic pennation angle measuring program and the manual pennation angle assessment method were 0.79, which indicated a significantly positive correlation (p<0.05). Conclusion: Pennation angle measurement using the automatic pennation angle measuring program showed acceptable reliability and validity. This study therefore demonstrated that the automatic measuring program was able to automatically measure the pennation angle of skeletal muscles using ultrasound images, and thus made it easy to investigate skeletal muscle architecture.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.525-533
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• 2022

We propose an effective method for suppressing both side and grating lobes by applying 2-dimensional Fourier Transform to the received channel data during the receive focusing process of an ultrasound imaging system. When the signal from the image point is focused, the channel signals have the same DC value across the channels. However, even after echoes from outside an imaging point are focused, they are manifested as having different spatial frequencies depending on their incident angles. Therefore, after the receive focusing delay time is applied, 2-D Fourier Transform is performed on the time-channel data to separate the DC component and other frequency components in the spectral domain, and the weighting value is defined using the ratio of the two values. The side lobe and grating lobe were suppressed by multiplying the ultrasound image by a weighting value. Ultrasound images with a frequency of 5 MHz were simulated in a 64-channel linear array. The grating lobe appearing in the ultrasound image was completely removed by applying the proposed method. In addition, the side lobe was reduced and the lateral resolution was greatly increased. Results of computer simulation on a human organ mimicking image show that the proposed method can aid in better lesion diagnosis by increasing the image contrast.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.1-8
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• 2021

Prostate cancer is one of the most diagnosed malignancies found across the world today. American cancer society in recent research predicted that over 174,600 new prostate cancer cases found and nearly 31,620 death cases recorded. Researchers are developing modest and accurate methodologies to detect and diagnose prostate cancer. Recent work has been done in radiology to detect prostate tumors using ultrasound imaging and resonance imaging techniques. Transrectal ultrasound and Magnetic resonance images of the prostate gland help in the detection of cancer in the prostate gland. The proposed paper is based on comparison and analysis between two novel image segmentation approaches. Seed region growing and cluster based image segmentation is used to extract the region from trans-rectal ultrasound prostate and MR prostate images. The region of extraction represents the abnormality area that presents in men's prostate gland. Detection of such abnormalities in the prostate gland helps in the identification and treatment of prostate cancer

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.118-127
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• 2024

Commonly deep learning methods for enhancing the quality of medical images use unpaired dataset due to the impracticality of acquiring paired dataset through commercial imaging system. In this paper, we propose a supervised learning method to enhance the quality of ultrasound images. The U-net model is designed by incorporating a divide-and-conquer approach that divides and processes an image into four parts to overcome data shortage and shorten the learning time. The proposed model is trained using paired dataset consisting of 828 pairs of low-quality and high-quality images with a resolution of 512x512 pixels obtained by varying the number of channels for the same subject. Out of a total of 828 pairs of images, 684 pairs are used as the training dataset, while the remaining 144 pairs served as the test dataset. In the test results, the average Mean Squared Error (MSE) was reduced from 87.6884 in the low-quality images to 45.5108 in the restored images. Additionally, the average Peak Signal-to-Noise Ratio (PSNR) was improved from 28.7550 to 31.8063, and the average Structural Similarity Index (SSIM) was increased from 0.4755 to 0.8511, demonstrating significant enhancements in image quality.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.141-149
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• 2003

This paper proposes a method of measuring and imaging the stiffness of human soft tissue to diagnose cancers or tumors which have been difficult to detect in ultrasound B-mode imaging systems. To measure the soft tissue stiffness, sinusoidal vibrations are applied to it, and the magnitude of its mechanical vibration is determined by estimating the temporal variation of speckle pattern brightness in ultrasound B-mode images. It is verified by simulation and experiment that the proposed method can estimate the relative tissue stiffness from B-mode images with a relatively small amount of computation.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.390-398
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• 2022

Ultrasound examination using ultrasound equipment is an ultrasound device that images human organs using sound waves and is used in various areas such as diagnosis, follow-up, and treatment of diseases. However, if the quality of ultrasound equipment is not guaranteed, the possibility of misdiagnosis increases, and the diagnosis rate decreases. Accordingly, The Korean Society of Radiology and Korea society of Ultrasound in Medicine presented guidelines for quality management of ultrasound equipment using ATS-539 phantom. The DenseNet201 classification algorithm shows 99.25% accuracy and 5.17% loss in the Dead Zone, 97.52% loss in Axial/Lateral Resolution, 96.98% accuracy and 20.64% loss in Sensitivity, 93.44% accuracy and 22.07% loss in the Gray scale and Dynamic Range. As a result, it is the best and is judged to be an algorithm that can be used for quantitative evaluation. Through this study, it can be seen that if quantitative evaluation using artificial intelligence is conducted in the qualitative evaluation item of ultrasonic equipment, the reliability of ultrasonic equipment can be increased with high accuracy.

• Progress in Medical Physics
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• v.31 no.3
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• pp.35-53
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• 2020

The authors congratulate the cerebrations for the 30 years of the Korean Society of Medical Physics (http://www.ksmp.or.kr/). The paper is published to recognize the anniversary. Geon-Ho Jahng invited Professor Z. H. Cho to join to submit this manuscript because he has been one of the leaders in the field of magnetic resonance imaging (MRI) during the last 40 years. In this review, we describe the development and clinical histories of MRI internationally and domestically. We also discuss diffusion and perfusion MRI, molecular imaging using MRI and MR spectroscopy (MRS), and the hybrid systems, such as positron emission tomography-MRI (PET-MRI), MR-guided focused ultrasound surgery (MRgFUS), and MRI-guided linear accelerators (MRI-LINACs). In each part, we discuss the historical evolution of the developments, technical developments, and clinical applications.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.87-99
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• 2002

This paper describes a method for overcoming the motion artifacts inherent in synthetic aperture(SA) imaging. based on the investigation results as to the influence of a target motion on synthetic aperture techniques. This method uses a region-based motion compensation approach in which only the axial motion is estimated and compensated for a given region of interest(ROI) under the assumption that the whole ROI moves uniformly The estimated axial motion is calculated with a crosscorrelation(CC) method at the Point where the focused signal has the maximum energy within the ROI. We also presents a method for estimating the axial motion using the autocorrelation(AC) method that is widely used to estimate average Doppler frequency Both computer simulations and in vivo experiments show that the proposed methods can improve greatly the spatial resolution and SNR of ultrasound imaging by implementing the SA techniques for two-way dynamic focusing without motion artifacts. In addition the AC-barred motion compensation method provides almost the same results as the CC-based one, but with a dramatically reduced computational complexity.

• Journal of the Korean Society of Physical Medicine
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• v.16 no.2
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• pp.45-52
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• 2021

PURPOSE: This study examined the imaging procedure of pectoralis minor muscle thickness and assessed the intra- and inter-rater reliability of the muscle thickness measured by two raters using rehabilitative ultrasound imaging (RUSI) in healthy individuals. METHODS: Fifteen participants (aged 21 - 28, seven females, and eight males) were involved in the study. The primary rater palpated the coracoid process and the fourth rib, defined as the width of the index finger lateral to the sternum to avoid breast tissues, and lined the two landmarks. The second examiner checked 1 / 3 (1st point) and 1 / 2 (2nd point) of the line length as measurement points. The two raters obtained right side muscle images of the participants at a standardized sitting position using RUSI with a 7.5 MHz linear transducer at 40mm depth. For intra-rater reliability, the principal rater took three images per point and tried to take one more with an interval. For the inter-rater reliability, the other rater performed the same tasks as the principal rater on the same day. The reliability was analyzed using the intra-class correlation coefficient (ICC), the standard error of the measurement (SEM), and Bland and Altman plots. RESULTS: The reliability at all points was excellent for the same rater (ICC_3,1 = .973 - .978, SEM = .042 - .046), and between raters (ICC_2,1 = .939 - .959, SEM = .059 - .097). CONCLUSION: These findings show that the RUSI could be reliable for examining the pectoralis minor muscle thickness in healthy individuals at all measurement sites.