Plane wave imaging combined with eigenspace-based minimum variance beamforming using a ring array in ultrasound computed tomography

A Signal Domain Object Segmentation Method for Ultrasound and Photoacoustic Computed Tomography

Image segmentation is important in improving the diagnostic capability of ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT), as it can be included in the image reconstruction process to improve image quality and quantification abilities. Segmenting the imaged object out of the background using image domain methods is easily complicated by low contrast, noise, and artifacts in the reconstructed image. Here, we introduce a new signal domain object segmentation method for USCT and PACT which does not require image reconstruction beforehand and is automatic, robust, computationally efficient, accurate, and straightforward. We first establish the relationship between the time-of-flight of the received first arrival waves and the object's boundary which is described by ellipse equations. Then, we show that the ellipses are tangent to the boundary. By looking for tangent points on the common tangent of neighboring ellipses, the boundary can be approximated with high fidelity. Imaging experiments of human fingers and mice cross-sections showed that our method provided equivalent or better segmentations than the optimal ones by active contours. In summary, our method greatly reduces the overall complexity of object segmentation and shows great potential in eliminating user dependency without sacrificing segmentation accuracy. The method can be further seamlessly incorporated into algorithms for other processing purposes in USCT and PACT, such as high-quality image reconstruction.

Effects of Beamforming Techniques on Quality of Ultrasound Computed Tomography Images

BACKGROUND

In body tissues, tumors generally have different speeds of sound (SOS) than normal tissues. In this respect, ultrasound computed tomography (UCT) can generate a cross-sectional SOS map as an innovative ultrasound imaging method. This technique can produce images with a resolution of millimeters and a high signal-to-noise ratio.

OBJECTIVE

This study aimed to improve UCT image quality without increasing breast cancer screening and diagnosis time.

MATERIAL AND METHODS

In this analytical study, a ring-shaped UCT breast imaging system was simulated using the K-wave toolbox of MATLAB. The system has a 20 cm diameter and 256 ultrasonic piezoelectrics placed in the ring's circumference. Different beamforming techniques imaged two designed phantoms (i.e., resolution and contrast), and the resolution and contrast to noise ratio (CNR) were calculated.

RESULTS

The results of resolution phantom imaging without any beamforming showed that only bars with the value of 0.125 and 0.167 lp/mm were distinguishable, and the 0.1 bars were not recognizable in the imaging. In addition, increasing the number of transmitters led to no noticeable change in resolution for 0.125 and 0.167 lp/mm bars. In all beamforming techniques for imaging the contrast phantom, the CNR parameter up to an object with a diameter of 8 mm increases with increasing diameter without any change.

CONCLUSION

The beamforming technique using three simultaneous transmitters improved the resolution by about 1 mm compared to the normal strategy. In addition to high-contrast images, beamforming with 9 simultaneous transmitters led to a preferable technique.

Design and Implementation of a Modular and Scalable Research Platform for Ultrasound Computed Tomography

Increasing attention has been attracted to the research of ultrasound computed tomography (USCT). This article reports the design considerations and implementation details of a novel USCT research system named UltraLucid, which aims to provide a user-friendly platform for researchers to develop new algorithms and conduct clinical trials. The modular design strategy is adopted to make the system highly scalable. A prototype has been assembled in our laboratory, which is equipped with a 2048-element ring transducer, 1024 transmit (TX) channels, 1024 receive (RX) channels, two servers, and a control unit. The prototype can acquire raw data from 1024 channels simultaneously using a modular data acquisition and a transfer system, consisting of 16 excitation and data acquisition (EDAQ) boards. Each EDAQ board has 64 independent TX and RX channels and 4-Gb Ethernet interfaces for raw data transmission. The raw data can be transferred to two servers at a theoretical rate of 64 Gb/s. Both servers are equipped with a 10.9-TB solid-state drive (SSD) array that can store raw data for offline processing. Alternatively, after processing by onboard field-programmable gate arrays (FPGAs), the raw data can be processed online using multicore central processing units (CPUs) and graphics processing units (GPUs) in each server. Through control software running on the host computer, the researchers can configure parameters for transmission, reception, and data acquisition. Novel TX-RX scheme and coded imaging can be implemented. The modular hardware structure and the software-based processing strategy make the system highly scalable and flexible. The system performance is evaluated with phantoms and in vivo experiments.