• Title/Summary/Keyword: Thyroid Ultrasound image

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Texture analysis of Thyroid Nodules in Ultrasound Image for Computer Aided Diagnostic system (컴퓨터 보조진단을 위한 초음파 영상에서 갑상선 결절의 텍스쳐 분석)

  • Park, Byung eun;Jang, Won Seuk;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.20 no.1
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    • pp.43-50
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    • 2017
  • According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

Ultrasound Image Classification of Diffuse Thyroid Disease using GLCM and Artificial Neural Network (GLCM과 인공신경망을 이용한 미만성 갑상샘 질환 초음파 영상 분류)

  • Eom, Sang-Hee;Nam, Jae-Hyun;Ye, Soo-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.956-962
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    • 2022
  • Diffuse thyroid disease has ambiguous diagnostic criteria and many errors occur according to the subjective diagnosis of skilled practitioners. If image processing technology is applied to ultrasound images, quantitative data is extracted, and applied to a computer auxiliary diagnostic system, more accurate and political diagnosis is possible. In this paper, 19 parameters were extracted by applying the Gray level co-occurrence matrix (GLCM) algorithm to ultrasound images classified as normal, mild, and moderate in patients with thyroid disease. Using these parameters, an artificial neural network (ANN) was applied to analyze diffuse thyroid ultrasound images. The final classification rate using ANN was 96.9%. Using the results of the study, it is expected that errors caused by visual reading in the diagnosis of thyroid diseases can be reduced and used as a secondary means of diagnosing diffuse thyroid diseases.

Evaluation of U-Net Based Learning Models according to Equalization Algorithm in Thyroid Ultrasound Imaging (갑상선 초음파 영상의 평활화 알고리즘에 따른 U-Net 기반 학습 모델 평가)

  • Moo-Jin Jeong;Joo-Young Oh;Hoon-Hee Park;Joo-Young Lee
    • Journal of radiological science and technology
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    • v.47 no.1
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    • pp.29-37
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    • 2024
  • This study aims to evaluate the performance of the U-Net based learning model that may vary depending on the histogram equalization algorithm. The subject of the experiment were 17 radiology students of this college, and 1,727 data sets in which the region of interest was set in the thyroid after acquiring ultrasound image data were used. The training set consisted of 1,383 images, the validation set consisted of 172 and the test data set consisted of 172. The equalization algorithm was divided into Histogram Equalization(HE) and Contrast Limited Adaptive Histogram Equalization(CLAHE), and according to the clip limit, it was divided into CLAHE8-1, CLAHE8-2. CLAHE8-3. Deep Learning was learned through size control, histogram equalization, Z-score normalization, and data augmentation. As a result of the experiment, the Attention U-Net showed the highest performance from CLAHE8-2 to 0.8355, and the U-Net and BSU-Net showed the highest performance from CLAHE8-3 to 0.8303 and 0.8277. In the case of mIoU, the Attention U-Net was 0.7175 in CLAHE8-2, the U-Net was 0.7098 and the BSU-Net was 0.7060 in CLAHE8-3. This study attempted to confirm the effects of U-Net, Attention U-Net, and BSU-Net models when histogram equalization is performed on ultrasound images. The increase in Clip Limit can be expected to increase the ROI match with the prediction mask by clarifying the boundaries, which affects the improvement of the contrast of the thyroid area in deep learning model learning, and consequently affects the performance improvement.

Ultrasonic Image Analysis Using GLCM in Diffuse Thyroid Disease (미만성 갑상샘 질환에서 GLCM을 이용한 초음파 영상 분석)

  • Ye, Soo-Young
    • Journal of the Korean Society of Radiology
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    • v.15 no.4
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    • pp.473-479
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    • 2021
  • The diagnostic criteria for diffuse thyroid disease are ambiguous and there are many errors due to the subjective diagnosis of experts. Also, studies on ultrasound imaging of thyroid nodules have been actively conducted, but studies on diffuse thyroid disease are insufficient. In this study, features were extracted by applying the GLCM algorithm to ultrasound images of normal and diffuse thyroid disease, and quantitative analysis was performed using the extracted feature values. Using the GLCM algorithm for thyroid ultrasound images of patients diagnosed at W hospital, 199 normal cases, 132 mild cases, and 99 moderate cases, a region of interest (50×50 pixel) was set for a total of 430 images, and Autocorrelation, Sum of squares, sum average, sum variance, cluster prominence, and energy were analyzed using six parameters. As a result, in autocorrelation, sum of squares, sum average, and sum variance four parameters, Normal, Mild, and Moderate were distinguished with a high recognition rate of over 90%. This study is valuable as a criterion for classifying the severity of diffuse thyroid disease in ultrasound images using the GLCM algorithm. By applying these parameters, it is expected that errors due to visual reading can be reduced in the diagnosis of thyroid disease and can be utilized as a secondary means of diagnosing diffuse thyroid disease.

Retrospective Analysis of Cytopathology using Gray Level Co-occurrence Matrix Algorithm for Thyroid Malignant Nodules in the Ultrasound Imaging (갑상샘 악성결절의 초음파영상에서 GLCM 알고리즘을 이용한 세포병리 진단의 후향적 분석)

  • Kim, Yeong-Ju;Lee, Jin-Soo;Kang, Se-Sik;Kim, Changsoo
    • Journal of radiological science and technology
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    • v.40 no.2
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    • pp.237-243
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    • 2017
  • This study evaluated the applicability of computer-aided diagnosis by retrospective analysis of GLCM algorithm based on cytopathological diagnosis of normal and malignant nodules in thyroid ultrasound images. In the experiment, the recognition rate and ROC curve of thyroid malignant nodule were analyzed using 6 parameters of GLCM algorithm. Experimental results showed 97% energy, 93% contrast, 92% correlation, 92% homogeneity, 100% entropy and 100% variance. Statistical analysis showed that the area under the curve of each parameter was more than 0.947 (p = 0.001) in the ROC curve, which was significant in the recognition of thyroid malignant nodules. In the GLCM, the cut-off value of each parameter can be used to predict the disease through analysis of quantitative computer-aided diagnosis.

Application of Texture Features algorithm using Computer Aided Diagnosis of Papillary Thyroid Cancer in the Ultrasonography (초음파영상에서 갑상선 결절의 컴퓨터자동진단을 위한 Texture Features 알고리즘 응용)

  • Ko, Seong-Jin;Lee, Jin-Soo;Ye, Soo-Young;Kim, Changsoo
    • The Journal of the Korea Contents Association
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    • v.13 no.5
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    • pp.303-310
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    • 2013
  • Thyroid nodular disease is the most frequently appeared in thyroid disease. Thyroid ultrasonography offers location of nodules, size, the number, information of internal echo characteristic. Thus, it makes possible to sort high-risk nodule containing high possibility about thyroid cancer and to induct precisely when take a Fine Needle Biopsy Aspiration. On thyroid nodule, the case which is diagnosed as malignant is less than 5% but screening test is very important on ultrasound and also must be reduced unnecessary procedure. Therefore, in this study an approach for describing a region is to quantity its texture content. We applied TFA algorithm on case which has been pathologically diagnosed as papillary thyroid cancer. we obtained experiment image which set the ROI on ultrasound and cut the $50{\times}50$ pixel size, histogram equalization. Consequently, Disease recognition detection efficiency of GLavg, SKEW, UN, ENT parameter were high as 91~100%. It is suggestion about possibility on CAD which distinguishes thyroid nodule. In addition, it will be helpful to differential diagnosis of thyroid nodule. If the study on additional parameter algorithm is continuously progressed from now on, it is able to arrange practical base on CAD and it is possible to apply various disease in the thyroid US.

Validation of Ultrasound and Computed Tomography-Based Risk Stratification System and Biopsy Criteria for Cervical Lymph Nodes in Preoperative Patients With Thyroid Cancer

  • Young Hun Jeon;Ji Ye Lee;Roh-Eul Yoo;Jung Hyo Rhim;Kyung Hoon Lee;Kyu Sung Choi;Inpyeong Hwang;Koung Mi Kang;Ji-hoon Kim
    • Korean Journal of Radiology
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    • v.24 no.9
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    • pp.912-923
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    • 2023
  • Objective: This study aimed to validate the risk stratification system (RSS) and biopsy criteria for cervical lymph nodes (LNs) proposed by the Korean Society of Thyroid Radiology (KSThR). Materials and Methods: This retrospective study included a consecutive series of preoperative patients with thyroid cancer who underwent LN biopsy, ultrasound (US), and computed tomography (CT) between December 2006 and June 2015. LNs were categorized as probably benign, indeterminate, or suspicious according to the current US- and CT-based RSS and the size thresholds for cervical LN biopsy as suggested by the KSThR. The diagnostic performance and unnecessary biopsy rates were calculated. Results: A total of 277 LNs (53.1% metastatic) in 228 patients (mean age ± standard deviation, 47.4 years ± 14) were analyzed. In US, the malignancy risks were significantly different among the three categories (all P < 0.001); however, CT-detected probably benign and indeterminate LNs showed similarly low malignancy risks (P = 0.468). The combined US + CT criteria stratified the malignancy risks among the three categories (all P < 0.001) and reduced the proportion of indeterminate LNs (from 20.6% to 14.4%) and the malignancy risk in the indeterminate LNs (from 31.6% to 12.5%) compared with US alone. In all image-based classifications, nodal size did not affect the malignancy risks (short diameter [SD] ≤ 5 mm LNs vs. SD > 5 mm LNs, P ≥ 0.177). The criteria covering only suspicious LNs showed higher specificity and lower unnecessary biopsy rates than the current criteria, while maintaining sensitivity in all imaging modalities. Conclusion: Integrative evaluation of US and CT helps in reducing the proportion of indeterminate LNs and the malignancy risk among them. Nodal size did not affect the malignancy risk of LNs, and the addition of indeterminate LNs to biopsy candidates did not have an advantage in detecting LN metastases in all imaging modalities.

Clinical Correlation between the Autoimmune Thyroid Disease for the Thyroid Autoimmune Antibodies and the Maximum Standardized Uptake Value: Base on the Hashimoto's Thyroiditis and the Graves' Disease (자가 면역 갑상선 질환에 대한 최대 표준섭취계수와 갑상선 자가 항체의 임상적 상관관계: 하시모토 갑상선염과 그레이브스병 중심으로)

  • Woo, Minsun;Baek, Chulin;Yoo, Jueun;Song, Jongwoo;Im, Inchul;Son, Juchul;Cho, Soodong;Lee, Jaeseung
    • Journal of the Korean Society of Radiology
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    • v.8 no.5
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    • pp.241-248
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    • 2014
  • The purpose of this study were to analyze the clinical correlation between the thyroid autoimmune antibodies (anti-TPO Ab, anti-TG Ab, and TSH) and the maximum standardized uptake value ($SUV_{max}$) base on the Hashimoto's thyroiditis and the Graves' disease in diffusely $^{18}F-FDG$ uptake of the thyroid gland to the PET/CT image. To achieve this, we was performed the PET/CT examination for the 1,097 subjects from May 2010 to April 2013 in the health screening, and was detected the diffused FDG thyroid uptake, and was additionally performed the thyroid function test (TFT) and the ultrasound (US). As a results, the autoimmune thyroid disease with the diffused FDG thyroid uptake were discovered 39 patients (3.9%), of this, the Hashimoto's thyroiditis was 43.6% and the Graves' disease was 23.1%. Hashimoto's thyroiditis was shown the positive reaction of high titer between the anti-TPO Ab and the anti-TG Ab level, and the correlation coefficient between the $SUV_{max}$ and the anti-TPO Ab was a statistically significant (r>04, p<0.05). Also, Graves' disease was shown the positive reaction of high titer most of the thyroid autoimmune antibodies, and the correlation coefficient between the $SUV_{max}$ and the anti-TPO Ab was a statistically significant (r>05, p<0.01). Therefor, when have a high standard of the $SUV_{max}$ due to the diffusely $^{18}F-FDG$ uptake of the thyroid gland, Hashimoto's thyroiditis and Graves' disease were proportionally increased the anti-TPO Ab and TSH level, respectively. The correlation coefficient between the $SUV_{max}$ and the thyroid autoimmune antibodies will be the most influential criterion that was a standard of judgment for the epihpenomenon of the autoimmune thyroid disease, and it will be available for the clinical application.

Literature Review of Clinical Studies for the Relationship between Ultrasonographic Examination and Syndrome Differentiation Classification in Chinese Medicine (초음파영상검사와 한의변증분류와의 관계와 관련된 중의학 임상연구에 대한 문헌고찰)

  • Hwang, Ji Hye;Ko, Dongkun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.32 no.4
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    • pp.217-225
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    • 2018
  • This study was to investigate the relationship between ultrasonographic examination and pattern identification classification on cinical studies in chinese medicine. We searched clinical studies related correlation between ultrasonographic examination and pattern identification classification in chinese medicine, that published from 2013 to 2016 in China National Knowledge Infrastructure (CNKI) databases by keywords, 'ultrasound(超?)', 'chinese medicine(中?)', 'syndrome differentiation (辨?)'. Seventeen studies were found. There were 7 studies of gynecological diseases including polycystic ovary syndrome and uterine myoma, 5 studies of fatty liver, 3 studies of arthritis, and 1 studie of thyroid nodule and lymphadenopathy respectively. As a result, ii is thought that there was a certain degree of correlation between the change of the ultrasonographic image and the pathological types according to traditional chinese medicine (TCM) syndrome differentiation and ultrasonographic examination could be used as secondary means for the TCM syndrome differentiation classification. In conclusion, by using ultrasonograph device in a medicinal way of TCM and traditional korean medicine (TKM), it is thought that more detailed and accurate diagnosis and treatment are possible and the evidence for reasonableness of syndrome differentiation in TCM and TKM its validity can be secured.

Diagnostic Usefulness of Digital Infrared Thermal Image in Carpal Tunnel Syndrome (수근관 증후군에서 적외선 체열 검사의 진단적 유용성)

  • Park, Jihyun;Lee, Jang Woo;Lee, Sang Eok;Kim, Byung Hee;Park, Dougho
    • Clinical Pain
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    • v.18 no.2
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    • pp.70-75
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    • 2019
  • Objective: The purpose of this study is to evaluate the usefulness of infrared thermography in patients with carpal tunnel syndrome by comparing with electrodiagnostic and ultrasonographic findings. Method: From January 2014 to October 2017, electrodiagnosis, ultrasound, and digital infrared thermal image (DITI) of unilateral carpal tunnel syndrome diagnosed in a single hospital were retrospectively analyzed. The subjects with bilateral symptoms of carpal tunnel syndrome, peripheral vascular disease, diabetes, thyroid disease, fibromyalgia, rheumatic disease, systemic infection, inflammation, malignant tumor, and other musculoskeletal disorders such as finger osteoarthritis, peripheral neuropathy, cervical radiculopathy, and the previous history of surgery were excluded. Results: Of 53 patients diagnosed with carpal tunnel syndrome, 11 were male and 42 were female. The visual analogue scale was 4.9 ± 1.9, and the duration of symptom was 11.8 ± 12.5 months. There was no statistically significant difference in the body surface temperature between the unaffected and affected sides. The severity of symptoms, electrodiagnostic findings, and cross-sectional area of the median nerve significantly correlates to each other. The temperature difference between the second fingers of the affected and unaffected sides showed a weak correlation with the amplitude of sensory nerve action potential and onset latency of compound muscle action potential, when there was no significant correlation with the other parameters. Conclusion: The difference in temperature on the surface of the body, which can be confirmed by DITI, is little diagnostic value when DITI is performed in unilateral carpal tunnel syndrome patients, especially when compared with ultrasonography.