Combination of variational mode decomposition and coherent factor for ultrasound computer tomography

Wang, Shanshan; Zou, Xinyi; Zeng, Liang; Song, Junjie; Zhou, Liang; Ding, Mingyue; Yuchi, Ming

doi:10.3233/thc-228016

Cited by 6 publications

(3 citation statements)

References 15 publications

(14 reference statements)

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“…Variational Mode Decomposition (VMD) technology, as an advanced signal processing method, has been extensively applied in the data processing field. Researchers like Wang S et al [12] have successfully combined VMD with coherence factor methods to significantly enhance the quality of ultrasound CT (USCT) images and effectively remove noise. In addressing the issue of speckle noise in ultrasound imaging, ref.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition

Jin,

Qian

2024

Electronics

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As the application of machine learning technology in predicting and optimizing material performance continues to grow, handling the electromagnetic data of magnetic materials, especially in removing unavoidable data noise and accurately extracting resonance peaks in the imaginary part of electromagnetic information, has become a significant challenge. These steps are crucial for revealing the deep electromagnetic behavior of materials and optimizing their performance. In response to this challenge, this study introduces an innovative approach—Genetic Algorithm-Optimized Variational Mode Decomposition for Signal Enhancement (GAO-VMD-SE). This method, through the Variational Mode Decomposition (VMD) technique optimized by genetic algorithms, not only effectively reduces noise in the data, thereby improving the Signal-to-Noise Ratio (SNR) and reducing the Mean Absolute Error (MAE), but also significantly enhances the hidden resonance peak information in complex permittivity and permeability data to achieve a comprehensive improvement in key performance indicators. Experimental results prove that this method surpasses traditional analysis techniques in key performance metrics such as the peak width ratio, peak overlap ratio, and the number of peaks. Especially in identifying characteristic peaks related to the Snoek limit, GAO-VMD-SE can effectively reveal the peak features hidden in complex data, thus providing important insights for evaluating the performance of materials at specific frequencies. Moreover, the effectiveness of this method in denoising not only enhances the quality and accuracy of material data analysis but also achieves a 1% to 10% enhancement in peak information extraction. This optimized data processing capability and versatility make GAO-VMD-SE not only suitable for evaluating the performance of magnetic materials but also show significant practical application value in processing spectral data and other time series signal data applications.

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Section: Related Workmentioning

confidence: 99%

Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition

Jin,

Qian

2024

Electronics

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“…The full width at half maximum (FWHM) 29 for a point of the ultrasound image usually represents the resolution. What’s more, the speckle signal-to-noise ratio (sSNR), 30 the contrast-noise ratio (CNR), 31 and the contrast ratio (CR) 32 are used to evaluate the cyst performance. The specific calculation is as follows:…”

Section: Imaging Setup and Image Quality Metricsmentioning

confidence: 99%

Improving Image Quality by Deconvolution Recovery Filter in Ultrasound Imaging

et al. 2022

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Due to the advantages of non-radiation and real-time performance, ultrasound imaging is essential in medical imaging. Image quality is affected by the performance of the transducer in an ultrasound imaging system. For example, the bandwidth controls the pulse length, resulting in different axial resolutions. Therefore, a transducer with a large bandwidth helps to improve imaging quality. However, large bandwidths lead to increased system cost and sometimes a loss of sensitivity and lateral resolution in attenuating media. In this paper, a deconvolution recovery method combined with a frequency-domain filtering technique (DRF) is proposed to improve the imaging quality, especially for the axial resolution. In this method, the received low-bandwidth echo signals are converted into high-bandwidth signals, which is similar to the echo signals produced by a high-bandwidth transducer, and the imaging quality is improved. Simulation and experiment results show that, compared with Delay-and-sum (DAS) method, the DRF method improved axial resolution from 0.60 to 0.41 mm in simulation and from 0.62 to 0.47 mm in the tissue-mimicking phantom experiment. The contrast ratio performance is improved to some extent compared with the DAS in experimental and in-vivo images. Besides, the proposed method has the potential to further improve image quality by combining it with adaptive weightings, such as the minimum variance method.

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“…While UT technology currently has limited clinical applications, its vast potential has garnered rapid attention in research. Initial and ongoing UT research has predominantly centered on the breast [6,7], emphasizing technology development, parameter optimization and image display [8]. This includes various studies involving phantom validation [9], preclinical studies of normal breasts and breast cancer in volunteers, as well as clinical trials [10].…”

mentioning

confidence: 99%

Clinical Application of Ultrasound Tomography in Diagnosis of Musculoskeletal Diseases

Cong,

Hui,

Tao

et al. 2024

Advanced Ultrasound in Diagnosis and Therapy

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To evaluate the feasibility and capability of UT in detecting musculoskeletal system lesions in the limbs and to explore its image quality. Materials and Methods:The Institutional Review Board has approved this prospective single-center study. This study included participants with various musculoskeletal and neurologic disorders in the limbs who provided written consent from October 2022 to April 2023. In addition to other radiological examinations (X-rays, CT, or MRI) and conventional handheld ultrasound scans requested by clinicians based on the conditions, each participant also underwent UT scanning using our developed limb ultrasound imaging system during the same period. Four radiologists and ultrasound physicians with more than five years of experience in musculoskeletal diagnostics analyzed the two-dimensional and three-dimensional images of the examination area.Results: Overall, 50 participants were evaluated (mean age, 36 years ± 18 [SD]; 26 males). The conditions included musculoskeletal tumors (n = 10), postoperative follow-up of musculoskeletal tumors (n = 20), peripheral nerve disorders in the limbs (n = 10) and postoperative pain in orthopedic surgery (n = 10). In all UT images, the region of interest was completely displayed, and internal structures such as muscles and nerves were clearly visible. Compared to conventional ultrasound images, the reconstructed three-dimensional images intuitively displayed the relationship between the lesions and surrounding tissues. Furthermore, UT did not exhibit metal artifacts when observing soft tissues around metallic implants, providing more comprehensive soft tissue information and more intuitive stereoscopic images. Conclusion:Clinical results of the UT system have demonstrated its feasibility as an automated and standardized imaging technique for musculoskeletal imaging, providing a new imaging modality for the diagnosis of musculoskeletal diseases in the human body.

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Combination of variational mode decomposition and coherent factor for ultrasound computer tomography

Cited by 6 publications

References 15 publications

Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition

Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition

Improving Image Quality by Deconvolution Recovery Filter in Ultrasound Imaging

Clinical Application of Ultrasound Tomography in Diagnosis of Musculoskeletal Diseases

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