Evaluation of Speckle Noise Reduction and Feature Enhancement in Prolapsed Mitral Valve Leaflet Echocardiography
01 Feb 2021-Vol. 1085, Iss: 1, pp 012033
TL;DR: A comparative analysis of well established despeckling filters compiled for speckle suppression and feature enhancement shows that feature enhanced Fast Non-Local Means (FNLM) filter outperforms other state-of-art filtering techniques in the aspect of higher PSNR value and preserves structural similarity in terms of SSIM value near to unity.
Abstract: Rheumatic heart disease has a substantial impact on morbidity and mortality for both men and women in developing countries. It is a complication of autoimmune phenomenon known as acute rheumatic fever in response to group A streptococcus bacteria. It often causes damage to valves and lacks its functionality. Initial manifestations of prolapsed valves are evident in echocardiography in the form of valve bulging, commissural fusion and restricted leaflet motion. However, these echocardiogram images are inevitably degraded by multiplicative noise known as speckle noise at the time of image acquisition and transmission. Hence despeckling is of vital importance for enhancing ultrasound image quality. In this paper, a comparative analysis of well established despeckling filters compiled for speckle suppression and feature enhancement has been performed. In addition to this, the performance of these filters is validated using different quantitative metrics. The experimental result shows that feature enhanced Fast Non-Local Means (FNLM) filter outperforms other state-of-art filtering techniques in the aspect of higher PSNR value and preserves structural similarity in terms of SSIM value near to unity. In conclusion, the preprocessing intends to suppress speckle noise and enhancing perceived visual quality that aids for further development of virtual cardiac model.
References
More filters
TL;DR: The data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented and the advantages and disadvantages of state-of-the-art approaches are discussed in detail.
Abstract: Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.
202 citations
TL;DR: An improved median filtering algorithm is proposed that reduces the noise and retains the details of the image and the complexity is decreased to O (N), and the performance of noise reduction has effectively improved.
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"Evaluation of Speckle Noise Reducti..." refers methods in this paper
...Median Filter Median Filter [17][18] which is used in our approach is a non linear filter based on order statistics....
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TL;DR: Performance of proposed method is superior to wavelet thresholding, bilateral filter and non-local means filter and superior/akin to multi-resolution bilateral filter in terms of method noise, visual quality, PSNR and Image Quality Index.
Abstract: Non-local means filter uses all the possible self-predictions and self-similarities the image can provide to determine the pixel weights for filtering the noisy image, with the assumption that the image contains an extensive amount of self-similarity. As the pixels are highly correlated and the noise is typically independently and identically distributed, averaging of these pixels results in noise suppression thereby yielding a pixel that is similar to its original value. The non-local means filter removes the noise and cleans the edges without losing too many fine structure and details. But as the noise increases, the performance of non-local means filter deteriorates and the denoised image suffers from blurring and loss of image details. This is because the similar local patches used to find the pixel weights contains noisy pixels. In this paper, the blend of non-local means filter and its method noise thresholding using wavelets is proposed for better image denoising. The performance of the proposed method is compared with wavelet thresholding, bilateral filter, non-local means filter and multi-resolution bilateral filter. It is found that performance of proposed method is superior to wavelet thresholding, bilateral filter and non-local means filter and superior/akin to multi-resolution bilateral filter in terms of method noise, visual quality, PSNR and Image Quality Index.
125 citations
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TL;DR: The presence of mild mitral regurgitation where the aetiology has been shown not to be due to chordal rupture, papillary muscle dysfunction secondary to coronary artery disease, rheumatic mitral valve disease, or Marfan's disease, may be consistent with full certification.
Abstract: Mitral stenosis is a progressive lesion carrying a relatively high risk of sudden incapacitation from systemic embolus or the onset of atrial fibrillation. Since the condition is likely to be significant when diagnosed, it is not compatible with single-crew professional operations and requires careful supervision. The presence of mild mitral regurgitation where the aetiology has been shown not to be due to chordal rupture, papillary muscle dysfunction secondary to coronary artery disease, rheumatic mitral valve disease, or Marfan's disease, where left atrial and left ventricular dimensions are shown to be normal on the echocardiogram, and where follow-up over at least a year has shown no progression of disease, may be consistent with full certification. Regular cardiological review with echocardiography and exercise electrocardiography is required. Any departure from these guidelines may lead to restriction of flying status to multi-crew operations, or denial.
75 citations
TL;DR: A new model is proposed that can remove speckle noise efficiently while suppress staircase effects on both synthetic images and real ultrasound images and achieves higher quality in terms of the peak signal to noise ratio and the structural similarity index.
Abstract: Speckle noise contamination is a common issue in ultrasound imaging system. Due to the edge-preserving feature, total variation (TV) regularization-based techniques have been extensively utilized for speckle noise removal. However, TV regularization sometimes causes staircase artifacts as it favors solutions that are piecewise constant. In this paper, we propose a new model to overcome this deficiency. In this model, the regularization term is represented by a combination of total variation and high-order total variation, while the data fidelity term is depicted by a generalized Kullback-Leibler divergence. The proposed model can be efficiently solved by alternating direction method with multipliers (ADMM). Compared with some state-of-the-art methods, the proposed method achieves higher quality in terms of the peak signal to noise ratio (PSNR) and the structural similarity index (SSIM). Numerical experiments demonstrate that our method can remove speckle noise efficiently while suppress staircase effects on both synthetic images and real ultrasound images.
70 citations