scholarly journals Frequency domain despeckling technique for medical ultrasound images

2021 ◽  
Vol 72 (4) ◽  
pp. 229-239
Author(s):  
Jawad F. Al-Asad ◽  
Hiren K. Mewada ◽  
Adil H. Khan ◽  
Nidal Abu-Libdeh ◽  
Jamal F. Nayfeh
Keyword(s):  
Frequency Domain ◽  
Signal To Noise Ratio ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Schur Decomposition ◽  
Visual Effects ◽  
Local Means ◽  
Non Local ◽  
The Time Domain

Abstract This work proposes a novel frequency domain despeckling technique pertaining to the enhancement of the quality of medical ultrasound images. The results of the proposed method have been validated in comparison to both the time-domain and the frequency-domain projections of the schur decomposition as well as with several other benchmark schemes such as frost, lee, probabilistic non-local means (PNLM) and total variation filtering (TVF). The proposed algorithm has shown significant improvements in edge detection and signal to noise ratio (SNR) levels when compared with the performance of the other techniques. Both real and simulated medical ultrasound images have been used to evaluate the numerical and visual effects of each algorithm used in this work.

Speckle reduction in medical ultrasound images using an unbiased non-local means method

2016 ◽  
Vol 28 ◽  
pp. 1-8 ◽  
Author(s):  
P.V. Sudeep ◽  
P. Palanisamy ◽  
Jeny Rajan ◽  
Hediyeh Baradaran ◽  
Luca Saba ◽  
...  
Keyword(s):  
Speckle Reduction ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Local Means ◽  
Non Local

Attenuation of seismic swell noise using convolutional neural networks in frequency domain and transfer learning

2020 ◽  
Vol 8 (4) ◽  
pp. T941-T952
Author(s):  
Jiachun You ◽  
Yajuan Xue ◽  
Junxing Cao ◽  
Canping Li
Keyword(s):  
Frequency Domain ◽  
Transfer Learning ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Structural Similarity ◽  
Fine Tuning ◽  
Network Parameter ◽  
Marine Seismic ◽  
The Time Domain

Because swell noises are very common in marine seismic data, it is extremely important to attenuate them to improve the signal-to-noise ratio (S/N). Compared to process noises in the time domain, we have built a frequency-domain convolutional neural network (CNN) based on the short-time Fourier transform to address swell noises. In the numerical experiments, we quantitatively evaluate the denoising performances of the time- and frequency-domain CNNs, compare the impacts of network structures on attenuating swell noises, and study how network parameter choices impact the quality of the denoised signal based on peak S/N, structural similarity, and root-mean-square-error indices. These results help us to build an optimal CNN model. Furthermore, to illustrate the superiority of our proposed method, we compare the conventional and proposed CNN methods. To address the generalization capability of CNN, we adopt transfer learning by using fine tuning to adjust the weights of the pretrained model with a small amount of target data. The application of transfer learning improves the quality of the denoised images, which further proves that our proposed method with transfer learning has the potential to be deployed in actual seismic data acquisition.

JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

2018 ◽  
Vol 12 (7-8) ◽  
pp. 76-83
Author(s):  
E. V. KARSHAKOV ◽  
J. MOILANEN
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Interval ◽  
Single Spectrum ◽  
Simultaneous Inversion ◽  
Homogeneous Half Space ◽  
Time Domain Data ◽  
The Time Domain

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

Denoising Ultrasound Medical Images

2017 ◽  
pp. 761-775
Author(s):  
A.S.C.S. Sastry ◽  
P.V.V. Kishore ◽  
Ch. Raghava Prasad ◽  
M.V.D. Prasad
Keyword(s):  
Image Quality ◽  
Medical Images ◽  
Ultrasound Image ◽  
Similarity Index ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Soft Thresholding ◽  
Block Based

Medical ultrasound imaging has revolutioned the diagnostics of human body in the last few decades. The major drawback of ultrasound medical images is speckle noise. Speckle noise in ultrasound images is because of multiple reflections of ultrasound waves from hard tissues. Speckle noise degrades the medical ultrasound images lessening the visible quality of the image. The aim of this paper is to improve the image quality of ultrasound medical images by applying block based hard and soft thresholding on wavelet coefficients. Medical ultrasound image transformation to wavelet domain uses debauchee's mother wavelet. Divide the approximate and detailed coefficients into uniform blocks of size 8×8, 16×16, 32×32 and 64×64. Hard and soft thresholding on these blocks of approximate and detailed coefficients reduces speckle noise. Inverse transformation to original spatial domain produces a noise reduced ultrasound image. Experiments on medical ultrasound images obtained from diagnostic centers in Vijayawada, India show good improvements to ultrasound images visually. Quality of improved images in measured using peak signal to noise ratio (PSNR), image quality index (IQI), structural similarity index (SSIM).

scholarly journals Casting Blanks Cleanliness Evaluation Based on Ultrasonic Microscopy and Morphological Filtering

Metals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 796
Author(s):  
Heng Ding ◽  
Qingting Qian ◽  
Xue Li ◽  
Zhu Wang ◽  
Min Li
Keyword(s):  
Signal To Noise Ratio ◽  
New Technology ◽  
Continuous Caster ◽  
Internal Quality ◽  
Ultrasound Images ◽  
Morphological Filtering ◽  
Ultrasound Technology ◽  
Metal Materials ◽  
Better Than

The cleanliness of the casting blanks could seriously affect the quality of downstream products. Recently, ultrasound technology has been introduced to detect the inclusions in metal materials. However, due to the anisotropy of the material crystal, the ultrasonic wave has the characteristics of multiple scattering and refraction in its propagation process. This makes it difficult to evaluate the casting blanks cleanliness effectively, for the inclusion echoes are submerged in the background noise. Therefore, the ultrasonic microscope is innovatively proposed to carry out efficient scanning on the casting blanks. In the meantime, the morphological filtering algorithm has the advantages of fewer parameters and faster calculation speed which can be used to increase the signal-to-noise ratio of ultrasound images and extract the defect features more efficiently. In order to verify the effectiveness of the proposed method, specimens were taken from three strands of continuous caster for detection and analysis. The experimental results show that the second strand has the best quality and the cleanliness is 2.2/mm3, which is obviously better than the other two strands. This method will provide a new technology for the quantitative evaluation of the internal quality of the casting blanks.

scholarly journals Speckle suppression in medical ultrasound images through Schur decomposition

2018 ◽  
Vol 12 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Adil H. Khan ◽  
Jawad F. Al-Asad ◽  
Ghazanfar Latif
Keyword(s):  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Schur Decomposition ◽  
Speckle Suppression

Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions

2014 ◽  
Author(s):  
Denis H. P. Salvadeo ◽  
Isabelle Bloch ◽  
Florence Tupin ◽  
Nelson D. A. Mascarenhas ◽  
Alexandre L. M. Levada ◽  
...  
Keyword(s):  
Ultrasound Images ◽  
Local Means ◽  
Non Local
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