The Research of Automatic Classification of Ultrasound Thyroid Nodules

作     者：Yanling An Shaohai Hu Shuaiqi Liu Jie Zhao Yu-Dong Zhang 

作者机构：Institute of Information ScienceBeijing Jiaotong UniversityBeijing100044China College of Electronic and Information EngineeringHebei UniversityBaoding071000China Machine Vision Technology Innovation Center of Hebei ProvinceBaoding071000China Department of InformaticsUniversity of LeicesterLeicesterLE17RHUK 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2021年第128卷第7期

页      面：203-222页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

基　　金：This work was supported in part by National Natural Science Foundation of China under Grant Nos.61572063 and 61401308 Natural Science Foundation of Hebei Province under Grant Nos.F2016201142,F2018210148,F2019201151 and F2020201025 Science Research Project of Hebei Province under Grant Nos.BJ2020030,QN2016085 and QN2017306 Foundation of President of Hebei University under Grant No.XZJJ201909 Opening Foundation of Machine Vision Technology Innovation Center of Hebei Province under Grant Nos.2018HBMV01 and 2018HBMV02 Natural Science Foundation of Hebei University under Grant Nos.2014-303 and 8012605 

主　　题：Thyroid nodules active contour model feature extraction image classification 

摘      要：This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs)and discriminate them as benign or malignant. The system firstly uses variational level set active contour withgradients and phase information to complete automatic extraction of the boundaries of thyroid nodules *** according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction methodbased on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, thispaper introduces a weight factor to improve support vector machine, offering different classes of samples withdifferent weights. Finally, thyroid nodules are classified and discriminated by the improved support vector *** show that the efficiency of discrimination on benign and malignant thyroid nodules is improved.