scholarly journals Multiplane wave imaging increases signal-to-noise ratio in ultrafast ultrasound imaging

2015 ◽  
Vol 60 (21) ◽  
pp. 8549-8566 ◽  
Author(s):  
Elodie Tiran ◽  
Thomas Deffieux ◽  
Mafalda Correia ◽  
David Maresca ◽  
Bruno-Felix Osmanski ◽  
...  
Keyword(s):  
Ultrasound Imaging ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Wave Imaging ◽  
Noise Ratio

scholarly journals Converting Coherence to Signal-to-noise Ratio for Enhancement of Adaptive Ultrasound Imaging

2019 ◽  
Vol 42 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Hideyuki Hasegawa ◽  
Ryo Nagaoka
Keyword(s):  
Ultrasound Imaging ◽  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Frame Rate ◽  
Signal To Noise ◽  
High Frame Rate ◽  
Ultrasonic Echo ◽  
Wave Imaging ◽  
Noise Ratio ◽  
Phantom Experiments

High-frame-rate ultrasound is an emerging technique for functional ultrasound imaging. However, the lateral spatial resolution and contrast in high-frame-rate ultrasound with an unfocused transmit beam are inherently lower than those in conventional ultrasonic imaging based on the line-by-line acquisition using a focused ultrasonic beam because of the low directivity of the transmit beam. Coherence-based beamforming methods were introduced in ultrasound imaging for improvement of image quality. Such methods improve the lateral spatial resolution using the coherence among ultrasonic echo signals received by individual transducer elements. In this study, a new method based on the signal-to-noise ratio (SNR) among the element echo signals was developed for enhancement of the effect of the coherence factor (CF), which was previously developed for improvement in spatial resolution and contrast. In the proposed method, a new factor, namely, SNR factor, was introduced, and the relationship between the previously developed CF and SNR factor was discussed. The proposed method was implemented in plane wave imaging, and the performance was evaluated by simulated and phantom experiments. In simulation, the lateral spatial resolution and contrast obtained with the conventional CF were 0.23 mm and 47.0 dB, respectively, which were significantly better than 0.39 mm and 15.3 dB obtained by conventional delay-and-sum (DAS) beamforming. Using the proposed method, the lateral spatial resolution and contrast were further improved to 0.12 mm and 69.8 dB, respectively. Similar trends were found also in phantom experiments.

scholarly journals Development Of A Nonlinear Frequency Compounding Method With Applications In Ultrasound Imaging And Thermometry

2021 ◽  
Author(s):  
Tyler Hornsby
Keyword(s):  
Ultrasound Imaging ◽  
Focused Ultrasound ◽  
Ex Vivo ◽  
Signal To Noise Ratio ◽  
Single Frequency ◽  
Temperature Sensitive ◽  
Nonlinear Frequency ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Temperature Maps

<div>Frequency compounding is an ultrasound imaging technique used to reduce artifacts and improve signal-to-noise-ratio (SNR). In this work a new nonlinear frequency compounding (NLFC) method was introduced, and its application in B-mode imaging and noninvasive thermometry was investigated. NLFC input frequencies were optimized to maximize speckle-signal-to-noise-ratio (SSNR) in a tissue mimicking phantom, and the method was then used to produce maps of the temperature sensitive change in backscattered energy of acoustic harmonics (<i>h</i>CBE) during heating of ex vivo porcine tissue with a focused ultrasound transducer. A <i>h</i>CBE-to-temperature calibration was also performed and temperature maps produced. Lastly, a comparative study of the NLFC and previously used nonlinear single frequency (NLSF) method was completed. By using the NLFC method it was concluded that SSNR of B-mode and backscattered energy images, SNR of <i>h</i>CBE maps, and temperature map agreement with a theoretical COMSOL based model were improved over the previously used NLSF method.</div>

scholarly journals Development Of A Nonlinear Frequency Compounding Method With Applications In Ultrasound Imaging And Thermometry

2021 ◽  
Author(s):  
Tyler Hornsby
Keyword(s):  
Ultrasound Imaging ◽  
Focused Ultrasound ◽  
Ex Vivo ◽  
Signal To Noise Ratio ◽  
Single Frequency ◽  
Temperature Sensitive ◽  
Nonlinear Frequency ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Temperature Maps

<div>Frequency compounding is an ultrasound imaging technique used to reduce artifacts and improve signal-to-noise-ratio (SNR). In this work a new nonlinear frequency compounding (NLFC) method was introduced, and its application in B-mode imaging and noninvasive thermometry was investigated. NLFC input frequencies were optimized to maximize speckle-signal-to-noise-ratio (SSNR) in a tissue mimicking phantom, and the method was then used to produce maps of the temperature sensitive change in backscattered energy of acoustic harmonics (<i>h</i>CBE) during heating of ex vivo porcine tissue with a focused ultrasound transducer. A <i>h</i>CBE-to-temperature calibration was also performed and temperature maps produced. Lastly, a comparative study of the NLFC and previously used nonlinear single frequency (NLSF) method was completed. By using the NLFC method it was concluded that SSNR of B-mode and backscattered energy images, SNR of <i>h</i>CBE maps, and temperature map agreement with a theoretical COMSOL based model were improved over the previously used NLSF method.</div>

scholarly journals An Investigation of Binary Coded Excitation Methods Using Golay Code Pairs for High Frequency Ultrasound Imaging

2021 ◽  
Author(s):  
Xuegang Su
Keyword(s):  
Ultrasound Imaging ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
High Frequency Ultrasound ◽  
Golay Code ◽  
Signal To Noise ◽  
Coded Excitation ◽  
High Frequency Ultrasound Imaging ◽  
Noise Ratio ◽  
Frequency Ultrasound

We are investigating the feasibility of binary coded excitation methods using Golay code pairs for high frequency ultrasound imaging as a way to increase the signal to noise ratio. I present some theoretical models used to simulate the coded excitation method and results generated from the models. A new coded excitation high frequency ultrasound prototype system was built to verify the simulation results. Both the simulation and the experimental results show that binary coded excitation can improve the signal to noise ratio in high frequency ultrasound backscatter signals. These results are confirmed in phantoms and excised bovine liver. If just white noise is considered, the encoding gain is 15dB for a Golay pair of length 4. We find the system to be very sensitive to motion (i.e. phase shift) and frequency dependent (FD) attenuation, creating sidelobes and degrading axial resolution and encoding gain. Methods to address these issues are discussed.

A Proposed Approach to De-speckle an Ultrasound Image using Anisotropic Filter by Generating Diffusion Tensor

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Poonam Chauhan ◽  
Vikas Kaushik
Keyword(s):  
Ultrasound Imaging ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Ultrasound Image ◽  
Similarity Index ◽  
Speckle Noise ◽  
The Body ◽  
Invasive Technique ◽  
Signal To Noise ◽  
Noise Ratio

Ultrasound imaging is a technique that is used to diagnose the diseases in medical field using radiology. US (ultrasound) imaging is a non -invasive technique and used for imaging of internal structure of the body without any kind of penetration which helps to identify the diseases that have probability and tissues. Many kinds of noises present in US images but the presence of speckle noise is a big challenge since last few years in biomedical field. Sometimes speckle noise becomes the part of information and vice-versa. So it becomes hard to find the disease for doctors. There are many de-speckled filters available for de-noising. This paper gives a proposed approach to de-speckled the US image using anisotropic diffusion filter by calculating the different numerical values like SSIM (structural similarity index), SNR (signal to noise ratio), MSE (mean square error), PSNR (peak signal to noise ratio), which results in coherence enhancement The proposed technique provides better and improved edge and coherence enhancement in ultrasound image data.

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