LV segmentation through the analysis of radio frequency ultrasonic images

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Abstract

LV segmentation is often an important part of many automated cardiac diagnosis strategies. However, the segmentation of echocardiograms is a difficult task because of poor image quality. In echocardiography, we note that radio-frequency (RF) signal is a rich source of information about the moving LV as well. In this paper, first, we will investigate currently used, important RF derived parameters: integrated backscatter coefficient(IBS), mean central frequency (MCF) and the maximum correlation coefficients (MCC) from speckle tracking. Second, we will develop a new segmentation algorithm for the segmentation of the LV boundary, which can avoid local minima and leaking through uncompleted boundary. Segmentations are carried out on the RF signal acquired from a Sonos7500 ultrasound system. The results are validated by comparing to manual segmentation results. © Springer-Verlag Berlin Heidelberg 2007.

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Yan, P., Jia, C. X., Sinusas, A., Thiele, K., O’Donnell, M., & Duncan, J. S. (2007). LV segmentation through the analysis of radio frequency ultrasonic images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4584 LNCS, pp. 233–244). Springer Verlag. https://doi.org/10.1007/978-3-540-73273-0_20

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