12 May 1995 Application of frequency-domain quantitative analysis in the diagnosis of cardiac diseases
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Abstract
Cardiac B-mode ultrasonic tissue characterization is designed to use the fluctuations in acoustic signals from the myocardium to differentiate normal from morbid tissues due to their characteristic texture attenuation. In our paper, we suggest a new way that is based on frequency-domain texture analysis to quantify tissue characterization. The results of our experiments indicate that three of the power spectrum features PSE, PSM and LT can describe the characterization of myocardiac tissue very well either in normal or in diseased condition. We select these three features together with another feature PSER derived by combining two PSE values to construct a multilayered neural network based on BP algorithm which acts as a classifier to diagnose automatically input image samples of various diseases after being trained with known samples. The performance of the classifier is very satisfactory. In short, our system opens a new way for the quantitative diagnostic detection of diverse diseases including coronary heart disease myocardial infarction (CHD-MI) and dilated cardiomyopathy (DC).
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Ying Sun, Ying Sun, Xinliang Li, Xinliang Li, Mengyang Liao, Mengyang Liao, Zhang Dong, Zhang Dong, Xinfang Wang, Xinfang Wang, Jia-en Wang, Jia-en Wang, Mingxing Xie, Mingxing Xie, } "Application of frequency-domain quantitative analysis in the diagnosis of cardiac diseases", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); doi: 10.1117/12.208679; https://doi.org/10.1117/12.208679
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