• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.389-396
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• 2015

The liver fibrosis is a disease we often see in clinical medicine, and the persistence and repeatition of inflammation and necrosis of liver cells continue for several years, and it is proceeded to cirrhosis. So decrease of death rate and prevalence rate by complications of cirrhosis and hepatocellular carcinoma is main task of clinical medicine by protection of chronic liver ailment patients from proceeding to cirrhosis and hepatocellular carcinoma. So this study tried to represent the ultrasonic image, blood test, the relationship with liver stiffness of diffuse liver ailment patients as numbers. This study was performed with patients from whom the image was taken by ultrasonic and 141 people who were treated by fibroscan, the basic data for blood test was obtained from the test results at the time when ultrasonic image and liver fibroscan was performed. The statistical analysis was performed by One-way analysis of variance(ANOVA) to verify difference between groups. The value of liver stiffness was increased in the order of normal, chronic liver disease and cirrhosis. As a results, ALT and Albumin have no statistical difference between object groups, and there are statistical differences in the results of ultrasonic decoding at age, AST, ALP, Bilirubin, PLT, PT, and kPa, and they are statistically meaningful(p<0.005). And the value of liver stiffness of chronic liver ailment was presented only as over 12.5kPa in other study, but it was represented as numbers for quantitative diagnosis by presenting average kPa threshold value according to disease in this study. And by presenting relationship of diagnosed results, it is considered that it could be used as first tool to diagnose chronic liver ailment patients according to their disease.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.205-211
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• 2017

There is a need for aggressive diagnosis and treatment in middle-aged and high-risk individuals who are more likely to progress from nonalcoholic fatty liver to hepatitis. In this study, nonalcoholic fatty liver was divided into severe, moderate, and severe, and classified by quantitative method using computer analysis of GLCM algorithm. The purpose of this study was to evaluate the characteristics of ultrasound images in the local fat avoidance region. Normal, mild, moderate, severe fatty liver, and focal fat sparing area, 80 cases, respectively. Among the parameters of the GLCM algorithm, the values of the Autocorrelation, Square of the deviation, Sum of averages and Sum of variances with high recognition rate of the liver ultrasound image were calculated. The average recognition rate of the GLCM algorithm was 97.5%. The result of local fat avoidance image analysis showed the most similar value to the normal parenchyma. Ultrasonography can be easily accessed by primary screening, but there may be differences in the accuracy of the test method or the correspondence of results depending on proficiency. GLCM algorithm was applied to quantitatively classify the degree of fatty liver. Local fat avoidance region was similar to normal parenchyma, so it could be predicted to be homogeneous liver parenchyma without fat deposition. We believe that GLCM computer image analysis will provide important information for differentiating not only fatty liver but also other lesions.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.693-699
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• 2023

Ultrasound is widely used in the medical field for non-destructive and non-invasive disease diagnosis. In order to improve the disease diagnosis accuracy of diagnostic medical images, improving spatial resolution is a very important factor. In this study, we aim to model the super resolution convolutional neural network (SRCNN) algorithm in ultrasound images and analyze its applicability in the medical diagnostic field. The study was conducted as an experimental study using Field II simulation and open source clinical liver hemangioma ultrasound imaging. The proposed SRCNN algorithm was modeled so that end-to-end learning can be applied from low resolution (LR) to high resolution. As a result of the simulation, we confirmed that the full width at half maximum in the phantom image using a Field II program was improved by 41.01% compared to LR when SRCNN was used. In addition, the peak to signal to noise ratio (PSNR) and structural similarity index (SSIM) evaluation results showed that SRCNN had the excellent value in both simulated and real liver hemangioma ultrasound images. In conclusion, the applicability of SRCNN to ultrasound images has been proven, and we expected that proposed algorithm can be used in various diagnostic medical fields.

• Journal of Biomedical Engineering Research
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• v.13 no.1
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• pp.33-38
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• 1992

A new approach to texture classification for quantitative ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix comprised the gray level difference along with a distances. From this run difference matrix, we defined several vectors and parameters such as DOD, DGD, DAD vector, SHP, SMO, SMG, LDE, LDEL etc. Each parameter values calculated in fatty, cirrhotic, normal and chronic hepatitic liver images were plotted in a plane and we found that RDM method was more sensitive to small structural changes than the conventional run length method and showed improved classification ability between the diseases.

• Journal of Biomedical Engineering Research
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• v.6 no.1
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• pp.5-12
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• 1985

In this paper Kalman filtering technique is applied to ultrasound signal to improve resolution capability, Ivhlch is in use of diagnostic imaging systems. The main advantage of Kalman filter algorithm for the analysis of reflected ultrasound signal is its recursive structure which can be easily adapted to tlme varing system. Because soft-tissues, such as liver, act as distributed acoustic low-pass filters which continually change the propagating pulse. tIne can put to practical use above advantage to find a suitable signal generallng model. In state-space description of the system, the 6th order system produces tl)e 1)esc spectral approximation to the source pulse As a result of spectrum analysis, 6th order estimator for two closely spaced ((p.5 mm) reflectors enhances resolution by 4dB-lOdB. By using this result, the possibility to detect even minute tumor is demonstrated.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.297-300
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• 2015

In medical ultrasonography, transit time and contrast enhancement patterns are considered as important parameters to analyze liver diseases. In many recent researches, time-intensity curves(TIC) have been used for calculating the transit time of the contrast agents. However, the intensity curve may include the variations which are caused by the micro-bubble effect of contrast agents. In this paper, we propose a complementary approach to diagnostic parameter extraction which utilizes a density information as well as the intensity data. The proposed technique improves the accuracy in extraction of the transit time and velocity of contrast agents for detection and characterization of focal liver lesions. Through the experiments using a set of clinical data, we show that the proposed methods can improve the reliability of the parametric image data.

• Journal of radiological science and technology
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• v.42 no.3
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• pp.187-194
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• 2019

The purpose of this study was to evaluate the pathologic results of hepatic parenchyma parameters such as liver parenchyma, liver surface, liver margin and liver, portal vein, spleen size, And to evaluate the usefulness of fibrosis progression and hepatic ultrasonography. The sensitivity, specificity, positive predictive value, and prognostic value according to the stage of fibrosis and grade of inflammation were divided into two groups according to the morphologic variable "A" through ultrasound and "B" We evaluated the predictive value and predicted the variables to evaluate fibrosis in clinical diagnosis and treatment of patients with chronic liver disease. The sensitivity and specificity of hepatic fibrosis in hepatic morphologic variables and other size variables were highest in liver surface and edge. The morphologic parameters used in the evaluation of fibrosis were clinically relevant in distinguishing the fibrosis stage from the results of liver biopsy.

• Journal of the Korean Society of Radiology
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• v.9 no.4
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• pp.227-234
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• 2015

In this paper, we studied possibility about application for CAD on diffuse liver disease through pixel texture analysis parameters(average gray level, skewness, entropy) which based statistical property brightness histogram and image analysis using brightness difference liver and kidney parenchyma. The experiment was set by ROI ($50{\times}50$ pixels) on liver ultrasound images.(non specific, fatty liver, liver cirrhosis) then, evaluated disease recognition rates using 4 types pixel texture analysis parameters and brightness gap liver and kidney parenchyma. As a results, disease recognition rates which contained average brightness, skewness, uniformity, entropy was scored 100%~96%, they were high. In brightness gap between liver and kidney parenchyma, non specific was $-1.129{\pm}12.410$ fatty liver was $33.182{\pm}11.826$, these were shown significantly difference, but liver cirrhosis was $-1.668{\pm}10.081$, that was somewhat small difference with non specific case. Consequently, pixel texture analysis parameter which scored high disease recognition rates and CAD which used brightness difference of parenchyma are very useful for detecting diffuse liver disease as well as these are possible to use clinical technique and minimize reading miss. Also, it helps to suggest correct diagnose and treatment.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.69-76
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• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

• Journal of KIISE
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• v.42 no.7
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• pp.910-918
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• 2015

This paper presents a parameter visualization technique to overcome the limitation of the naked eye in contrast-enhanced ultrasonography. A method is also proposed to compensate for the distortion and noise in ultrasound image sequences. Meaningful parameters for diagnosing liver disease can be extracted from the dynamic patterns of the contrast enhancement in ultrasound images. The visualization technique can provide more accurate information by generating a parametric image from the dynamic data. Respiratory motions and noise from micro-bubble in ultrasound data may cause a degradation of the reliability of the diagnostic parameters. A multi-stage algorithm for respiratory motion tracking and an image enhancement technique based on the Markov Random Field are proposed. The usefulness of the proposed methods is empirically discussed through experiments by using a set of clinical data.