Automated segmentation of heart wall using coherence among ultrasonic rf echoes

In conventional ultrasonic tomographic images, the heart wall cannot be distinguished from the cardiac lumen automatically on the basis of only the echogenicity. One of the biggest problems is that echogenicity, which corresponds to the amplitude of an RF echo, in the heart wall is as low as that in the lumen. In this study, ultrasonic RF echoes from the heart wall and lumen were analyzed in the frequency domain in order to distinguish the heart wall from the lumen automatically. Temporal changes in complex frequency spectra were evaluated using the magnitude-squared coherence function. The coherence function of RF signals scattered from the interventricular septum (IVS) was high. In contrast, the coherence function in the right ventricle (RV) and left ventricle (LV) was low because the scatterers (blood cells) slipped off from the focal area of the ultrasonic beam by blood flow. For automated identification of the heart wall using the coherence function, the optimal threshold T ₀(f) for the coherence function should be determined. In this study, on the basis of the Bayes decision rule, the optimum value of T₀(f) was determined. The coherence function of the region near the anterior wall in the RV was as high as that in the IVS because there are artifacts in the region near the anterior wall owing to echoes from the external tissue resulting from the sidelobe. However, the artifacts can be reduced by removing the stationary component from RF echoes before evaluating the coherence function. In vivo experimental results show that the differentiation of the heart wall from the lumen was improved significantly using the proposed method.