Objectives The purpose of this study was to determine if the ultrasonic integrated backscatter and echo intensity could be used in clinical diagnosis of acute myocardial infarction. Methods and Results Within 2 weeks ...Objectives The purpose of this study was to determine if the ultrasonic integrated backscatter and echo intensity could be used in clinical diagnosis of acute myocardial infarction. Methods and Results Within 2 weeks after acute myocardial infarction,35 patients underwent ultrasonic tissue characterization from the papillary short - axis view. The cyclic variation of integrated backscatter and echo intensity of three different myocardial regions perfused by left anterior descending coronary artery, left circumflex coronary and right coronary were measured . The value of cyclic variation of integrated backscatter and integrated backscatter and echo intensity≤ half of the highest value of three different myocardial regions on a same view were define as the criteria for diagnosing acute myocardial infarction , and the results were compared with coronary angiography. The sensitivity of diagnosing acute myocardial infarction by both Ultrasonic tissue characterization with integrated backscatter and echo intensity were 91. 43 % . The location of myocardial infarction detected by this tech-nique corresponded with the damaged myocardial region determined by coronary angiography. Conclusions Ultrasonic tissue characterization with integrated backscatter and echo intensity could clinically be used as a noninvasive approach in the diagnosis of acute myocardial infarction.展开更多
A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the tra...A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the transducer on echoes is reduced greatly and the flaw features stand out more clearly in the deconvolved echoes than in flaw echoes themselves. flaw echo signals of 18 flaw samples are processed by adaptive filtering deconvolution. As a result, flaws are classified successfully展开更多
基金This work was supported by a grant from Chongqing ScienceCommittee (1997) 22-41.
文摘Objectives The purpose of this study was to determine if the ultrasonic integrated backscatter and echo intensity could be used in clinical diagnosis of acute myocardial infarction. Methods and Results Within 2 weeks after acute myocardial infarction,35 patients underwent ultrasonic tissue characterization from the papillary short - axis view. The cyclic variation of integrated backscatter and echo intensity of three different myocardial regions perfused by left anterior descending coronary artery, left circumflex coronary and right coronary were measured . The value of cyclic variation of integrated backscatter and integrated backscatter and echo intensity≤ half of the highest value of three different myocardial regions on a same view were define as the criteria for diagnosing acute myocardial infarction , and the results were compared with coronary angiography. The sensitivity of diagnosing acute myocardial infarction by both Ultrasonic tissue characterization with integrated backscatter and echo intensity were 91. 43 % . The location of myocardial infarction detected by this tech-nique corresponded with the damaged myocardial region determined by coronary angiography. Conclusions Ultrasonic tissue characterization with integrated backscatter and echo intensity could clinically be used as a noninvasive approach in the diagnosis of acute myocardial infarction.
文摘A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the transducer on echoes is reduced greatly and the flaw features stand out more clearly in the deconvolved echoes than in flaw echoes themselves. flaw echo signals of 18 flaw samples are processed by adaptive filtering deconvolution. As a result, flaws are classified successfully
