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A thyroid nodule classification method based on TI-RADS
Author(s): Hao Wang; Yang Yang; Bo Peng; Qin Chen
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Paper Abstract

Thyroid Imaging Reporting and Data System(TI-RADS) is a valuable tool for differentiating the benign and the malignant thyroid nodules. In clinic, doctors can determine the extent of being benign or malignant in terms of different classes by using TI-RADS. Classification represents the degree of malignancy of thyroid nodules. TI-RADS as a classification standard can be used to guide the ultrasonic doctor to examine thyroid nodules more accurately and reliably. In this paper, we aim to classify the thyroid nodules with the help of TI-RADS. To this end, four ultrasound signs, i.e., cystic and solid, echo pattern, boundary feature and calcification of thyroid nodules are extracted and converted into feature vectors. Then semi-supervised fuzzy C-means ensemble (SS-FCME) model is applied to obtain the classification results. The experimental results demonstrate that the proposed method can help doctors diagnose the thyroid nodules effectively.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042041 (21 July 2017); doi: 10.1117/12.2281600
Show Author Affiliations
Hao Wang, Southwest Jiaotong Univ. (China)
Yang Yang, Southwest Jiaotong Univ. (China)
Bo Peng, Southwest Jiaotong Univ. (China)
Qin Chen, Univ. of Electronic Science and technology of Medicine (China)
Sichuan Province People’s Hospital (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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