Real-time imaging is a major advantage of medical ultrasound technology and a challenging feature for other clinical imaging modalities to match. Ultrasound computed tomography (USCT), a novel ultrasound imaging technique that has recently gained considerable attention, offers high-resolution, 3D imaging without radiation. However, the amount of data generated by a USCT imaging system is overwhelming, and traditional GPU acceleration methods can be time-consuming due to data transfer and processing. To address these issues, a high-speed multi-channel parallel computing architecture is necessary. This paper presents a real-time USCT reflection imaging system. The system features a circular ring array with 2048 elements, a data acquisition system comprising 512 transmit and receive channels, and a computer equipped with a field-programmable gate array (FPGA) accelerator card. Radio frequency data are acquired by the data acquisition system and transmitted to the FPGA accelerator card via a quad channel 10-gigabit Ethernet interface. The accelerator card processes the data using full-aperture tomography to perform parallel reconstruction tasks. The prototype implementation, verified on an Xilinx KU115 FPGA, achieves a processing throughput of 8 frames per second (2.10 ×10⁶ pixels per second for a frame size of 512 ×512 pixels). The results of in vivo imaging experiments demonstrate the excellent image quality of the system and its real-time imaging capabilities.

Reflection Ultrasound Computed Tomography (UCT) is gaining prominence as an essential instrument for breast cancer screening. However, reflection UCT quality is often compromised by the variability in sound speed across breast tissue. Traditionally, reflection UCT utilizes the Delay and Sum (DAS) algorithm, where the Time of Flight significantly affects the coherence of the reflected radio frequency (RF) data, based on an oversimplified assumption of uniform sound speed. This study introduces three meticulously engineered modules that leverage the spatial correlation of receiving arrays to improve the coherence of RF data and enable more effective summation. These modules include the self-supervised blind RF data segment block (BSegB) and the state-space model-based strong reflection prediction block (SSM-SRP), followed by a polarity-based adaptive replacing refinement (PARR) strategy to suppress sidelobe noise caused by aperture narrowing. To assess the effectiveness of our method, we utilized standard image quality metrics, including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Root Mean Squared Error (RMSE). Additionally, coherence factor (CF) and variance (Var) were employed to verify the method’s ability to enhance signal coherence at the RF data level. The findings reveal that our approach greatly improves performance, achieving an average PSNR of 19.64 dB, an average SSIM of 0.71, and an average RMSE of 0.10, notably under conditions of sparse transmission. The conducted experimental analyses affirm the superior performance of our framework compared to alternative enhancement strategies, including adaptive beamforming methods and deep learning-based beamforming approaches.

Focused ultrasound (FU) technology is extensively employed in clinical applications such as tumor ablation, Parkinson’s disease treatment, and neuropathic pain management. The safety and efficacy of FU therapy critically depend on the accurate quantification of the acoustic field, particularly the high-pressure distribution in focal region. To address the limitations of existing acoustic measurement techniques—including invasiveness, inability to measure high sound pressure, and system complexity—this study proposes a non-invasive method termed Laser Deflection Acoustic Field Quantification (LDAQ), based on the laser deflection principle. An experimental system was constructed utilizing the acousto-optic deflection effect, which incorporates precision displacement control, rotational scanning, and synchronized triggering. Through tomographic scanning, laser deflection images of the acoustic field were acquired at multiple orientations. An inversion algorithm using Radon transforms was proposed to reconstruct the refractive index gradient distributions from the variations of light intensity and spot displacement. An adaptive weighted fusion strategy was then employed to map these optical signals to the sound pressure field. To validate the LDAQ technique, an acoustic field generated by an FU transducer operating at 0.84 MHz was measured. The reconstructed results were compared with both hydrophone measurements and numerical simulations. The findings demonstrated high consistency among all three results within the focal zone. Full-field analysis yielded a root mean square error (RMSE) of 0.1102 between LDAQ and simulation, and an RMSE of 0.1422 between LDAQ and hydrophone measurements. These results confirm that LDAQ enables non-invasive and high-precision quantification of megapascal-level focused acoustic fields, offering a reliable methodology for acoustic field characterization to support FU treatment optimization and device standardization.

Core parameters of the Musculoskeletal Ultrasound Computed Tomography System (MUCTS), such as spatial resolution, slice thickness, and three-dimensional reconstruction volume error, directly determine imaging performance and clinical diagnostic accuracy. To objectively and systematically assess the imaging quality and diagnostic reliability of this device, this study took the MUCTS developed by Weishi Medical Imaging Co., Ltd., as the test object. Multidimensional performance tests were carried out using standard ultrasound phantoms and polyurethane-based tissue-mimicking musculoskeletal phantoms. Under unified imaging and reconstruction parameters, key indicators, including effective detection radius, axial resolution, lateral resolution, imaging dead zone, slice thickness, geometric position accuracy, and three-dimensional reconstruction volume error, were quantitatively measured, and compliance verification was performed against product technical specifications. The test results demonstrated that the nominal center frequency was 3 MHz with a measured frequency deviation of 3%, and the effective detection radius reached 90 mm. Within the valid imaging range, the axial resolution was 0.5 mm, lateral resolution was 1 mm, imaging dead zone was 1 mm, and slice thickness was 3.2 mm. The relative error of geometric position accuracy was 3%, the relative deviations in perimeter and area measurements were both −1%, and the relative deviation in three-dimensional reconstructed volume was −8%. All indicators satisfied product technical requirements. Qualitative comparative experiments on tissue-mimicking phantoms confirmed that the system could reproduce multiscale and multi-contrast musculoskeletal anatomical features, and the acquired images showed favorable consistency with designed phantom targets. In conclusion, this musculoskeletal ultrasound tomographic system exhibits stable imaging performance and credible quantitative measurements, and can meet clinical and research demands for tomographic imaging and three-dimensional reconstruction of human musculoskeletal tissues.

Full-waveform inversion (FWI) typically employs finite-difference time-domain (FDTD) methods to solve the wave equation under the point-source assumption. For computational efficiency, the coarsest grid that satisfies dispersion and stability requirements is generally preferred. However, this grid may not resolve the finite aperture and spatial phase characteristics of a transducer, thereby introducing imaging artifacts and errors. This paper proposes an Operator-consistent reduced source that maps a local fine-grid radiation field to node-specific forcing histories for a prescribed coarse-grid operator. These histories are reused in repeated simulations without online fine-grid computation. On a 0.50 mm grid, the method reduced root-mean-square (RMS) field relative error by 96.4% compared with the Direct coarse-grid aperture source. In controlled FWI with independent observations, the sound-speed root-mean-square error was 2.14 m/s, compared with 4.94 and 5.17 m/s for the Point source and the Direct coarse-grid aperture source, respectively. Hydrophone measurements, blind ring-water validation, and three repeated phantom acquisitions further assessed field reproduction and reconstruction performance. The method enables coarse-grid FDTD simulations to represent the radiated fields of finite-aperture transducers whose device-scale features are not directly resolved by the target grid.