• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.757-759
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• 2004

본 연구에서는 초음파 영상에서 간실질의 에코 명도를 비롯한 픽셀 정보분포를 분석하여 정량화 지방간 진단 파라미터를 구하기 위해 규준화 에코 명도 값 및 다수의 텍스쳐 파라미터 값을 추출하여 선형결합을 통해 지방간의 진행 정도와의 상관성을 연구하였다. 임상 지방간 지수와 본 연구의 추정 지방간 지표 값과의 선형 상관계수를 구하였다 신장대조 방법으로 추출한 규준화 에코 명도 및 회색도 픽셀분포의 텍스쳐 특성 파라미터를 계산하여 임상결과와 비교한 결과 임상 지방간 지수와 높은 상관성을 보임을 알 수 있었고, 지방간 진단의 보조사료로 유용함을 확인하였다. 계산된 지방간 지수와 임상결과 간의 선형상관계수는 0.84-0.93이다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.16-23
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• 2020

In High-Intensity Focused Ultrasound (HIFU) treatment, effective localization of HIFU focus is important for developing a safe treatment plan. While Magnetic Resonance Imaging guided HIFU (MRIgHIFU) can visualize the ultrasound path during the treatment for localizing HIFU focus, it is challenging in ultrasound imaging guided HIFU (USIgHIFU). In the present study, a real-time ultrasound beam visualization technique capable of localizing HIFU focus is presented for USIgHIFU. In the proposed method, a short pulse, with the same center frequency of an imaging ultrasound transducer below the regulated acoustic intensity (i.e., Ispta < 720 mW/㎠), was transmitted through a HIFU transducer whereupon backscattered signals were received by the imaging transducer. To visualize the HIFU beam path, the backscattered signals underwent dynamic receive focusing and subsequent echo processing. From in vitro experiments with bovine serum albumin gel phantoms, the HIFU beam path was clearly depicted with low acoustic intensity (i.e., Ispta of 94.8 mW/㎠) and the HIFU focus was successfully localized before any damages were produced. This result indicates that the proposed ultrasound beam path visualization method can be used for localizing the HIFU focus in real time while minimizing unwanted tissue damage in USIgHIFU treatment.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.398-403
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• 2007

초음파 영상은 미세한 명암도 차이 등에 의해 분석 과정에서 근육 영역의 위치와 크기를 판단하는데 어려움이 발생하고 이로 인해 근육 영역을 파악하는데 주관성이 개입된다. 본 논문에서는 근육영역을 객관적으로 분석하기 위해 ART2 신경망을 적용하여 양자화를 수행한 후, 국부적 영역에서 근육 영역을 추출한다. 초음파 영상에서 히스토그램 평활화와 엔드인 탐색 알고리즘을 적용하여 명암도의 분포와 밝기 값을 보정 한 후, ART2 신경망을 이용하여 유사한 영역을 클러스터링 한다. 그리고 클러스터링 된 각 영역의 크기, 위치 및 명암도 정보를 분석하여 피하지방, 근육 막, 기타 배경 영역으로 분류한다. 최종적인 근육 영역을 찾기 위해 근육 막 내부 객체들 간의 거리, 각도를 이용하여 근육 막 영역에 둘러싸인 근육 영역을 추출한다. 실제 초음파 영상을 대상으로 실험한 결과, 일반적인 클러스터링 기법을 적용한 방법 보다 ART2 기반 양자화와 제안된 영역 확장 기법으로 근육영역을 추출하고 분석하는 것이 효율적임을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.11-17
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• 2014

While safe and convenient, ultrasound imaging analysis is often criticized by its subjective decision making nature by field experts in analyzing musculoskeletal system. In this paper, we propose a new automatic method to extract muscle area using ART2 neural network based quantization. A series of image processing algorithms such as histogram smoothing and End-in search stretching are applied in pre-processing phase to remove noises effectively. Muscle areas are extracted by considering various morphological features and corresponding analysis. In experiment, our ART2 based Quantization is verified as more effective than other general quantization methods.

• Journal of the Korean Society of Radiology
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• v.6 no.3
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• pp.183-189
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• 2012

Ultrasonography is one of the fields on the imaging studies within intra-abdominal organs. A blood test is a typical method of clinical chemical examination on the in vivo test of clinical symptoms. Fatty liver is performed simultaneously two kinds of diagnostics methods, intra-abdominal ultrasound and blood tests. At an implementing this, the standard of blood tests value was the TBIL, TC, AST, ALT, ALP, GGT, TG, HDL-C, GLU. In this study analyzing the accuracy of the two kinds of test, ultrasonography and blood test, on patients with fatty liver. From January to March 2012, patients 459 determined fatty liver within 1350, who received health examination simultaneously on the intra-abdominal ultrasonography and blood tests. Same result of ultrasonography and blood test's patients were 459 ie, 60.8%. and different result of those examinations was 280 ie, 39.2%. Consequently diagnostic accuracy was 60.8%. It presumably caused by differences in the diagnostic performance of ultrasound professionals(Radiologist or Radiological Technologist). In order to overcome this, ongoing educational and study will be needed.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.547-555
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• 2019

The purpose of this study was to evaluate the usefulness of routine liver ultrasonography on the basis of the scoring system according to the morphological parameters of liver ultrasound images and the histopathological results of liver biopsy. The morphological parameters of the liver through ultrasonography were divided into liver surface, liver edge and liver parenchyma. Pathologic results of liver biopsy were classified as mild fibrosis(F1), significant fibrosis(F2), severe fibrosis(F3), and cirrhosis(F4). In conclusion, routine ultrasound examination showed a sensitive predictive factor for fibrosis with mild fibrosis (F1) to severe fibrosis (F3) were liver edge>liver parenchyma>liver surface. However, the predictive factors for detecting cirrhosis (F4) were liver parenchyma>liver surface>liver edge. The use of three variable combinations rather than individual variables in routine ultrasonography may be useful in evaluating the degree and progress of liver fibrosis.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.911-917
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• 2023

The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.463-465
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• 2004

베디드 시스템의 발전으로 인하여 고성능화, 소형화, 편의성 등이 강조되어 지는 시점에서 의료장비 또한 임베디드 시스템 기술 도입이 빠르게 진행되어 지고 있다. 본 논문에서는 초음파 영상진단 단말기 (Magic-Probe)를 구현하기 위해 SA-1100 마이크로 프로세스 레퍼런스 보드에 리눅스 커널을 포팅하고 포팅된 플랫폼을 기반으로 초음파 영상진단을 처리하기 위한 응용프로그램의 설계 및 구현에 관하여 논하도록 하겠다.