|Table of Contents|

Breast tumor classification algorithm based on ultrasoundradio frequency signal(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2018年04期
Page:
385-
Research Field:
Publishing date:

Info

Title:
Breast tumor classification algorithm based on ultrasoundradio frequency signal
Author(s):
Yan Yu12aZhu Wei2aCai Runqiu2aCai Xiaowei2aZhang Hong1Li Qianmu1Wu Yiyun2b
1.School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China; 2.a. Medical Equipment Department; b. Ultrasound Medical Department,Affiliated Hospital Nanjing University of TCM(Jiangsu Province Hospital of TCM),Nanjing 210029,China
Keywords:
breast tumor radio frequency signals region of interest entropy standard deviation breast imaging reporting and data system image reconstruction classification
PACS:
TP391.7
DOI:
10.14177/j.cnki.32-1397n.2018.42.04.001
Abstract:
To solve the problem of quantitative classification of breast tumor ultrasound,an evaluation algorithm for quantitative classification of breast tumor is proposed from the perspective of ultrasonic radio frequency(RF)signal. Using breast imaging reporting and data system(BI-RADS)as the classification basis,the extracted RF data are reconstructed and segmented to acquire the region of interest(ROI)and its characteristic parameters of entropy and standard deviation are acquired. This paper quantifies the relationship between the characteristic parameters and the classification of lesion,and achieves the quantitative classification of breast tumor level 3,level 4 and level 5 with a classification success rate of 84.9%. The results show that the ultrasound RF signals have important implications for clinical diagnosis. Entropy and standard deviation can effectively achieve the classification of breast tumor ultrasound.

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Last Update: 2018-08-30