The use of thyroid ultrasound imageing texture features in diagnosing the nature of thyroid solid nodules
SONG Ge-sheng
LIU Wen-hui
LI Jin-ye
ZHANG Cheng-qi
Abstract：Objective To evaluate the value of using texture‐based gray‐level co‐occurrence matrix (GLCM ) features ex‐tracted from thyroid ultrasound images to build logistic model for differentiating the nature of thyroid nodules .Methods We collected 94 cases patients who suffered from the thyroid nodules and accepted thyroidectomy .GLCM was used to ex‐tract texture features from their ultrasound images .Then ,we used the features as independent variables and the nature of nodules as dependent variables to build logistic model .10‐fold cross‐validation was used to evaluate the performance of the model and drew the ROC curve .Results The accuracy of the logistic regression was 82% ,and the area under the ROC curve(AUC)was 0 .89 .Conclusion The binary logistic regression built with GLCM features extracted from solid thyroid ultrasound images is useful in diagnosing the nature of thyroid solid nodules .
Keywords：UltrasoundGLCMLogistic regressionSolid thyroid nodulesDifferential diagnosis
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 612-616 )