Speckle Reduction in Ultrasound Images of the Common Carotid Artery Based on Integer and Fractional-Order Total Variation

Abstract

Designing a technique with higher speckle noise suppressing capability, better edge preserving performance, and lower time complexity is a research objective for the common carotid artery (CCA) ultrasound despeckling. Total variation based techniques have been widely used in the image denoising and have good performance in preserving the edges in the images. However, the total variation based filters can produce the staircase artifacts. To address this issue, second-order total variation based techniques have been proposed for the image denoising. However, the previous study has been proved that the fractional differential model has better performance in reducing the speckles in ultrasound despeckling compared with the second-order model. Thus, to improve the performance of ultrasound despeckling and edge preserving, a novel despeckling model based on integer and fractional-order total variation (IFOTV) is proposed for CCA ultrasound images. Moreover, the minimization problems in our despeckling model are solved by the alternating direction method of multiplier (ADMM). In results with synthetic images, the edge preservation index (EPI) values of proposed method are 0.9524, 0.8797, and 0.7351 as well as 0.9137, 0.8253, and 0.6847 under three different levels of noise, which are the highest among four advanced methods. In results with simulated CCA ultrasound images, the speckle suppression and mean preservation indices of proposed method are 0.5596, 0.6571, and 0.8106 under three different levels of noise, which are the best among four advanced methods. In results with clinical images, the average absolute error of intima-media thickness measurements of proposed method is 0.0660 ± 0.0679 (mean ± std in mm), which is the lowest among four advanced methods. In conclusion, the IFOTV method has improved performance in suppressing the speckle noise and preserving the edge, and is thus a potential alternative to the current filters for the CCA ultrasound despeckling.

Total variation‐based ultrasound image despeckling using method noise thresholding in non‐subsampled contourlet transform

“…The small details over the high‐textured area are adequately retained; however, compared with other methods, the results are lacking. The result of applying fractional‐order total variation 27 can be seen in Figure 2D. The findings of Ref.…”

“…The findings of Ref. 27 are good; however, the despeckling is not up to the standard in places with a consistent level of noise. The smoothness of the homogenous sections is satisfactory, but the visually appealing appearance needs to be improved by increasing the smoothness of the more speckled regions.…”

“…To evaluate the performance of the proposed work using a reference image, we can use performance metrics, such as PSNR, 54 SSIM, 10 and correlation coefficient (CC) 13 . A variety of current and recent methodologies such as PDE, 23 non‐local variational (NLV) method, 24 fractional‐order total variation, 27 PCA‐based non‐local means, 28 wavelet‐based generative adversarial network 29 and adaptive wavelet thresholding 35 are employed in the comparative analysis. Existing techniques' best‐value parameters are used to make a fair comparison.…”

“…Small details over the high‐textured area are kept, but the results are inadequate. Figure 3D shows the FTV 27 result. The results of 27 are good; however, the despeckling is subpar in noisy areas.…”

“…Image despeckling approach based on second‐order total variation has been developed to overcome the problem of speckle reduction. It has been shown in prior research, however, the used fractional differential model outperforms the second‐order model in terms of minimizing speckle noise 27 . Kernel PCA‐NLM‐based despeckling for ultrasound images has been suggested in Ref.…”