A novel quantitative measurement for thyroid cancer detection based on elastography
At present, the widely methods used to evaluate elastograms clinically are color score and strain ratio. The color score is a qualitative measure estimated by radiologists, and its high subjectiveness may lead to error. Although the strain ratio is a quantitative method, the region selected to calculate the value is subjective and its accuracy is still quite low. A new effective, accurate, and quantitative metric using computer aided diagnosis (CAD) techniques is proposed in this paper. The statistical features and texture features are extracted from the lesion region on the elastogram. The important and reliable features are selected by using Minimum-Redundancy-Maximum-Relevance (mRMR) algorithm. The selected features were input to the SVM to classify the thyroid nodules. The experiment results confirm that the method is more accurate and robust than color score and strain ratio.
Thyroid nodule Elastography mRM SVM
Jianrui Ding H.D.Cheng Jianhua Huang Yingtao Zhang RD.Cheng Chunping Ning
School of Computer Science and Technology Harbin Institute of Technology Harbin, China Department of Computer Science Utah State University Logan, USA Department of Ultrasound Second Affiliated Hospital of Harbin Medical University Harbin, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
1831-1834
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）