In full waveform inversion (FWI) for ultrasound computed tomography (CT), choosing the right sound source is essential for generating high-resolution images. We developed an optimized source estimation method for FWI to efficiently reduce the value of any cost function and evaluated its performance using simulation data and measurement data. In our optimized source estimation method, we obtain the sound source as α(k)·f, where f is a sound source (an arbitrary complex value), coefficient α(k) is cos(θk)+i·sin(θk), k is integer (0, 1, ⋯, N-1), θk is 2π/N·k, and the integer value of N is 360. We then determine the coefficient α(k) that minimizes the value of the cost function. In contrast to conventional source estimation, which only minimizes the value of the L2 norm cost function, our proposed source estimation can minimize the values of any cost function, such as the L1 norm or a hybrid of L1 and L2 norms. The advantage of our method is that it can be easily applied to FWI with various cost functions. In this preliminary study, we implemented FWI with the L2 norm cost function and compared the performance of our proposed method with that of the conventional method. In the simulation study, FWI with both the conventional and proposed source estimation methods improved the contrasts of inclusions of a numerical phantom compared to FWI with no source estimation. They both also improved the contrasts of inclusions of a measured oil-gel-based phantom compared to a bent-ray reconstruction method. The absolute mean errors between ROI and true values were 39, 11, and 11 [m/s] for the bent-ray reconstruction method, FWI with the conventional method, and FWI with the proposed method, respectively. In addition, FWI with both the conventional and proposed methods improved the contrasts of a patient’s tumor compared to the bentray reconstruction method. These results demonstrate that FWI with the proposed source estimation method can provide the same contrast and quantitative accuracy as FWI with the conventional source estimation method.
We are performing clinical studies on breast cancer examinations at Hokkaido University Hospital with an ultrasound computed tomography (USCT) system. Our studies have revealed that some reflection images exhibit intensity inhomogeneity because ultrasound waves, shot by a 1-D ring array transducer, go non-vertically into the object surface. This trend significantly increases the burden of interpretation. Therefore, we developed a calibration method to remove this heterogeneity based on the distribution of the incident angle of waves that are estimated from the slope of the subject surface morphologically extracted from multi-slice reflection images. Results showed that applying this correction method to clinical images enabled the image contrast and uniformity to be successfully recovered.
Ultrasound Computed Tomography is a very promising medical imaging technology to be used to discover breast cancer early. The conventional ultrasound emission method (fan beam), which utilizes a single element for one emission, might result in a signal-to-noise ratio (SNR) too low for measuring dense breasts. This research proposes a virtual fan emission method that can maintain high accuracy, a large field of view, and a high SNR at the same time, using multiple elements while mimicking the wave field of single element emission. We experimentally proved its effectiveness in improving SNR by imaging a phantom with high attenuation to mimic a dense breast. Imaging of excised human breast tissues also suggested that the proposed virtual fan beam emission is more effective than conventional fan beam emission to screen for breast cancer correctly.