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In this paper we propose a computer-aided diagnosis system for the breast lesion classification. Our approach is based on quantitative ultrasound and deep learning. We used the Nakagami imaging to create parametric maps of breast lesions that illustrate tissue scattering properties. For this task the sliding window technique was applied. The Nakagami parameter was calculated using the maximum likelihood...
In this paper we investigate how to assess the ultrasound nonlinearity coefficient using plane wave imaging. We employ the technique based on excitation of the medium with ultrasonic pulses of increasing amplitude level. As the pulse pressure is increased, due to medium nonlinearity, higher fraction of energy is transferred from the fundamental to higher harmonics during the propagation. In this case...
The aim of the study was finding the relationship between BIRADS classification combined with envelope K and Nakagami statistics of the echoes backscattered in the breast tissue in vivo and the histological data. 107 breast lesions were examined. Both, the RF echo-signal and B-mode images from the lesions and surrounding tissue were recorded. The analysis method was based on the combining data from...
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