A method for evaluating the benign and malignant breast tumors based on radio?frequency(RF)data was explored by extracting the characteristic parameters of breast ultrasound RF signals.The breast biopsy data were used...A method for evaluating the benign and malignant breast tumors based on radio?frequency(RF)data was explored by extracting the characteristic parameters of breast ultrasound RF signals.The breast biopsy data were used as the reference data for judging the lump benign or malignant.The extracted ultrasound RF data were reconstructed and segmented by computer aided method to obtain the breast tumor region of interest(ROI)and its characteristic parameters(entropy and standard deviation).The characteristic parameters were statistically analyzed to evaluate the relationship between characteristic parameters and benign or malignant breast tumors.The results indicate the entropy and standard deviation of normal region is much higher than that of lump region,which shows that the standard deviation and entropy characteristic parameters of ultrasonic RF signals are meaningful in the diagnosis of breast tumors.The proposed method provides a new direction for computer?aided diagnosis of benign and malignant breast tumors.展开更多
基金financially supported by the National Natural Science Foundation of China (No. 61703201)the National Natural Science Foundation of Jiangsu Province (No. BK20170765)
文摘A method for evaluating the benign and malignant breast tumors based on radio?frequency(RF)data was explored by extracting the characteristic parameters of breast ultrasound RF signals.The breast biopsy data were used as the reference data for judging the lump benign or malignant.The extracted ultrasound RF data were reconstructed and segmented by computer aided method to obtain the breast tumor region of interest(ROI)and its characteristic parameters(entropy and standard deviation).The characteristic parameters were statistically analyzed to evaluate the relationship between characteristic parameters and benign or malignant breast tumors.The results indicate the entropy and standard deviation of normal region is much higher than that of lump region,which shows that the standard deviation and entropy characteristic parameters of ultrasonic RF signals are meaningful in the diagnosis of breast tumors.The proposed method provides a new direction for computer?aided diagnosis of benign and malignant breast tumors.
