  Breast cancer is the most prevalent cancer with a high mortality rate in
women over the age of 40. Many studies have shown that the detection of cancer
at earlier stages significantly reduces patients' mortality and morbidity
rages. Ultrasound computer tomography (USCT) is considered as a promising
screening tool for diagnosing early-stage breast cancer as it is cost-effective
and produces 3D images without radiation exposure. However, USCT is not a
popular choice mainly due to its prolonged imaging time. USCT is time-consuming
because it needs to transmit a number of ultrasound waves and record them one
by one to acquire a high-quality image. We propose FastUSCT, a method to
acquire a high-quality image faster than traditional methods for USCT. FastUSCT
consists of three steps. First, it transmits multiple ultrasound waves at the
same time to reduce the imaging time. Second, it separates the overlapping
waves recorded by the receiving elements into each wave with UNet. Finally, it
reconstructs an ultrasound image with a synthetic aperture method using the
separated waves. We evaluated FastUSCT on simulation on breast digital
phantoms. We trained the UNet on simulation using natural images and
transferred the model for the breast digital phantoms. The empirical result
shows that FastUSCT significantly improves the quality of the image under the
same imaging time to the conventional USCT method, especially when the imaging
time is limited.
