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Efficient implementation of ultrasound waveform tomography using data blending

Ultrasound waveform tomography is a promising tool for breast cancer characterization. However, the method is very time-consuming for large datasets acquired using a synthetic-aperture ultrasound tomography system consisting of hundreds to thousands of transducer elements. We introduce a data blending approach to ultrasound waveform tomography to greatly improves the computational efficiency. This method simultaneously simulates ultrasound waves emitted from multiple transducer elements. A random phase is applied to each source to distinguish the effect of different sources. The random phase helps eliminate the unwanted cross interference produced by different sources. This approach greatly reduces the computation time of ultrasound waveform tomography to one tenth of that for the original ultrasound waveform tomography.