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http://dx.doi.org/10.7742/jksr.2021.15.4.473

Ultrasonic Image Analysis Using GLCM in Diffuse Thyroid Disease  

Ye, Soo-Young (Department of Radiological Science, Catholic University of Pusan)
Publication Information
Journal of the Korean Society of Radiology / v.15, no.4, 2021 , pp. 473-479 More about this Journal
Abstract
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.
Keywords
Diffuse Thyroid Disease; Thyroid Ultrasonography; GLCM algorithm;
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