Basic research on elimination of artifacts in ultrasonic imaging based on spatiotemporal CMRF model

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Ultrasonic imaging provides us with a wide range of advantages in various application fields such as medical diagnosis and submarine measurement. The ultrasonic wave is, however, often affected by the artifacts caused by multipath effect, refraction, diffraction, and sidelobes in the wave propagation. The aim of this study is to establish a basis to identify and eliminate the artifacts adaptively by processing observed ultrasonic images with complex-valued neural networks (CVNNs). The basic idea includes the complex-valued Markov random field (CMRF) model and the CVNNs, which we proposed and have been investigated for these years. The CVNNs is an extension of neural networks so that we can deal with wave-related phenomena adaptively and flexibly with explicit phase variables. We adopt the CVNNs to treat complex-valued image data obtained in acoustic imaging for the identification and elimination of the artifact. This project have yielded the following remarkable achievements.(1)System … More construction in which we observe complex-amplitude of reflection and/or scattering of pseudo-continuous wave: We have constructed an ultrasonic surface measurement system with which we assume a clear boundary where the acoustic impedance changes abruptly, which is an ordinary case of seabed landscape observation. We transmit 50-wave packet and detect the received waveform, which is A/D converted and Fourier transformed, and we obtain the amplitude and phase of the carrier frequency component precisely.(2)Development and demonstration of a novel method of phase singular point elimination: When we construct a phase map from the data obtained in the above system, we find dense phase singular points (SPs) included there. We need to reduce the SPs and unwrap the phase. First we proposed a new method to unwrap the phase, namely, "spread singularity phase unwrapping." The calculation cost is lower and the quality of the digital elevation map (DEM) is higher than those of conventional methods. Secondly we developed a novel SP reduction method, i.e., "CMRF-based PS restoration method." We applied the method at respective SPs to make them move to their counterparts to get canceled out. It has been found that the method realizes both a large reduction rate and an accurate phase reservation, which lead directly to high quality generation of DEM. Less