scholarly journals Fast Super-Resolution Ultrasound Imaging With Compressed Sensing Reconstruction Method and Single Plane Wave Transmission

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 39298-39306 ◽  
Author(s):  
Yuexia Shu ◽  
Changpeng Han ◽  
Minglei Lv ◽  
Xin Liu
Keyword(s):  
Compressed Sensing ◽  
Plane Wave ◽  
Ultrasound Imaging ◽  
Super Resolution ◽  
Wave Transmission ◽  
Reconstruction Method ◽  
Single Plane

A new combined prior based reconstruction method for compressed sensing in 3D ultrasound imaging

2015 ◽  
Author(s):  
Muhammad S. Uddin ◽  
Rafiqul Islam ◽  
Murat Tahtali ◽  
Andrew J. Lambert ◽  
Mark R. Pickering
Keyword(s):  
Compressed Sensing ◽  
Ultrasound Imaging ◽  
3D Ultrasound ◽  
Reconstruction Method

Temporal Super-resolution of Ultrasound Imaging Using Matrix Completion

2020 ◽  
Vol 42 (3) ◽  
pp. 115-134 ◽  
Author(s):  
Mina Hosseinpour ◽  
Hamid Behnam ◽  
Maryam Shojaeifard
Keyword(s):  
Ultrasound Imaging ◽  
Spatial Information ◽  
Matrix Completion ◽  
Super Resolution ◽  
Frame Rate ◽  
Low Rank ◽  
Reconstruction Method ◽  
3D Data ◽  
Reconstruction Methods ◽  
2D And 3D

The temporal super-resolution of the dynamic ultrasound imaging, a means to observe rapid heart movements, is considered an important subject in medical diagnosis of cardiac conditions. Here, a new technique based on the acquisition scheme using the matrix completion (MC) theory is offered for the temporal super-resolution of the two-dimensional (2D) and three-dimensional (3D) ultrasound imaging. MC mentions the problem of completing a low-rank matrix when only a subset of its elements can be observed. Here, the lower scan lines are acquired. Whereby, the proposed method uses temporal and spatial information of the radio frequency (RF) image sequences for the reconstruction of skipped RF lines. This is performed using the construction of the MC images and then reconstruction of them by the MC theory. The results of the proposed method are compared with the compressive sensing (CS) reconstruction methods. The qualitative and quantitative evaluations of 2D and 3D data demonstrate that in the proposed method, which uses the spatial and temporal relation of RF images and the MC theory, the reconstruction is more accurate, and the reconstruction error is lower. The computational complexity of this method is very low. It also does not require hardware adjustments. Therefore, it can be easily implemented in current ultrasound-imaging devices with the frame-rate enhancement. For instance, the frame rate up to two times the original sequence is feasible using the proposed methods, while root mean square error is decreased by about 35% and 30% for 2D and 3D data, respectively, compared with the CS reconstruction method.

scholarly journals Compressed sensing-based super-resolution ultrasound imaging for faster acquisition and high quality images

2020 ◽  
Author(s):  
Jihun Kim ◽  
Qingfei Wang ◽  
Siyuan Zhang ◽  
Sangpil Yoon
Keyword(s):  
Image Quality ◽  
Compressed Sensing ◽  
Ultrasound Imaging ◽  
Imaging Technique ◽  
Super Resolution ◽  
Tumor Model ◽  
Acquisition Time ◽  
Mouse Tumor ◽  
Conventional Ultrasound

AbstractSuper-resolution ultrasound (SRUS) imaging technique has overcome the diffraction limit of conventional ultrasound imaging, resulting in an improved spatial resolution while preserving imaging depth. Typical SRUS images are reconstructed by localizing ultrasound microbubbles (MBs) injected in a vessel using normalized 2-dimensional cross-correlation (2DCC) between MBs signals and the point spread function of the system. However, current techniques require isolated MBs in a confined area due to inaccurate localization of densely populated MBs. To overcome this limitation, we developed the ℓ1-homotopy based compressed sensing (L1H-CS) based SRUS imaging technique which localizes densely populated MBs to visualize microvasculature in vivo. To evaluate the performance of L1H-CS, we compared the performance of 2DCC, interior-point method based compressed sensing (CVX-CS), and L1H-CS algorithms. Localization efficiency was compared using axially and laterally aligned point targets (PTs) with known distances and randomly distributed PTs generated by simulation. We developed post-processing techniques including clutter reduction, noise equalization, motion compensation, and spatiotemporal noise filtering for in vivo imaging. We then validated the capabilities of L1H-CS based SRUS imaging technique with high-density MBs in a mouse tumor model, kidney, and zebrafish dorsal trunk, and brain. Compared to 2DCC, and CVX-CS algorithm, L1H-CS algorithm, considerable improvement in SRUS image quality and data acquisition time was achieved. These results demonstrate that the L1H-CS based SRUS imaging technique has the potential to examine the microvasculature with reduced acquisition and reconstruction time of SRUS image with enhanced image quality, which may be necessary to translate it into the clinics.

Dynamic Transmit–Receive Beamforming by Spatial Matched Filtering for Ultrasound Imaging with Plane Wave Transmission

2017 ◽  
Vol 39 (4) ◽  
pp. 207-223 ◽  
Author(s):  
Yuling Chen ◽  
Yang Lou ◽  
Jesse Yen
Keyword(s):  
Experimental Data ◽  
Plane Wave ◽  
Ultrasound Imaging ◽  
Diffraction Theory ◽  
Frame Rate ◽  
Lateral Resolution ◽  
Matched Filtering ◽  
Single Plane ◽  
Depth Limit ◽  
Imaging Depth

During conventional ultrasound imaging, the need for multiple transmissions for one image and the time of flight for a desired imaging depth limit the frame rate of the system. Using a single plane wave pulse during each transmission followed by parallel receive processing allows for high frame rate imaging. However, image quality is degraded because of the lack of transmit focusing. Beamforming by spatial matched filtering (SMF) is a promising method which focuses ultrasonic energy using spatial filters constructed from the transmit–receive impulse response of the system. Studies by other researchers have shown that SMF beamforming can provide dynamic transmit–receive focusing throughout the field of view. In this paper, we apply SMF beamforming to plane wave transmissions (PWTs) to achieve both dynamic transmit–receive focusing at all imaging depths and high imaging frame rate (>5000 frames per second). We demonstrated the capability of the combined method (PWT + SMF) of achieving two-way focusing mathematically through analysis based on the narrowband Rayleigh–Sommerfeld diffraction theory. Moreover, the broadband performance of PWT + SMF was quantified in terms of lateral resolution and contrast from both computer simulations and experimental data. Results were compared between SMF beamforming and conventional delay-and-sum (DAS) beamforming in both simulations and experiments. At an imaging depth of 40 mm, simulation results showed a 29% lateral resolution improvement and a 160% contrast improvement with PWT + SMF. These improvements were 17% and 48% for experimental data with noise.

scholarly journals Study on the Application of Super-Resolution Ultrasound for Cerebral Vessel Imaging in Rhesus Monkeys

2021 ◽  
Vol 12 ◽  
Author(s):  
Li Yan ◽  
Chen Bai ◽  
Yu Zheng ◽  
Xiaodong Zhou ◽  
Mingxi Wan ◽  
...  
Keyword(s):  
Blood Flow ◽  
Plane Wave ◽  
Ultrasound Imaging ◽  
Rhesus Monkeys ◽  
Super Resolution ◽  
Transcranial Ultrasound ◽  
Cerebral Microvessels ◽  
Resolution Imaging ◽  
Large Animals

Background: Ultrasound is ideal for displaying intracranial great vessels but not intracranial microvessels and terminal vessels. Even with contrast agents, the imaging effect is still unsatisfactory. In recent years, significant theoretical advances have been achieved in super-resolution imaging. The latest commonly used ultrafast plane-wave ultrasound Doppler imaging of the brain and microbubble-based super-resolution ultrasound imaging have been applied to the imaging of cerebral microvessels and blood flow in small animals such as mice but have not been applied to in vivo imaging of the cerebral microvessels in monkeys and larger animals. In China, preliminary research results have been obtained using super-resolution imaging in certain fields but rarely in fundamental and clinical experiments on large animals. In recent years, we have conducted a joint study with the Xi'an Jiaotong University to explore the application and performance of this new technique in the diagnosis of cerebrovascular diseases in large animals.Objective: To explore the characteristics and advantages of microbubble-based super-resolution ultrasound imaging of intracranial vessels in rhesus monkeys compared with conventional transcranial ultrasound.Methods: First, the effectiveness and feasibility of the super-resolution imaging technique were verified by modular simulation experiments. Then, the imaging parameters were adjusted based on in vitro experiments. Finally, two rhesus monkeys were used for in vivo experiments of intracranial microvessel imaging.Results: Compared with conventional plane-wave imaging, super-resolution imaging could measure the inner diameters of cerebral microvessels at a resolution of 1 mm or even 0.7 mm and extract blood flow information. In addition, it has a better signal-to-noise ratio (5.625 dB higher) and higher resolution (~30-fold higher). The results of the experiments with rhesus monkeys showed that microbubble-based super-resolution ultrasound imaging can achieve an optimal resolution at the micron level and an imaging depth >35 mm.Conclusion: Super-resolution imaging can realize the monitoring imaging of high-resolution and fast calculation of microbubbles in the process of tissue damage, providing an important experimental basis for the clinical application of non-invasive transcranial ultrasound.

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