Ultrasound Medical Image Speckle Reduction Using Fourth-Order Partial Differential Equation

Keikhosravi, Adib; Hashemi-Berenjabad, Seyyedhadi

doi:10.1109/iranianmvip.2011.6121544

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Keikhosravi et al [14] implemented Fourth-Order Partial Differential Equation for US medical image speckle reduction. The range of speckle noise from 0.05 to 0.3.…”

Section: Pde Waveletmentioning

confidence: 99%

Despeckleing Prostate Ultrasonograms Using Pde With Wavelet

Ramesh¹,

Manavalan²

2018

IJIVP

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Prostate cancer is the leading cause of death for men, since the cause of the disease is mysterious and its early detection is also monotonous. Ultrasound (US) is the most popular tool to detect the human organ glands and also used to diagnose the prostate cancer. Speckle noise is an inherent nature of ultrasound images, which degrades the image quality. So far, No specific filter is available to suppress the speckle noise in prostate image. In this paper, a novel despeckling method PDE with Wavelet is presented for prostate US images. The enhancement method is evaluated by using standard measures like Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR) and Edge Preservation Index (EPI). Further, the despeckling approaches' is also evaluated time and space complexity. From the results, it is observed that the filtering method PDE with Wavelet is superior to PDE in terms of denoising and also preserving the information content.

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“…Keikhosravi et al [14] implemented Fourth-Order Partial Differential Equation for US medical image speckle reduction. The range of speckle noise from 0.05 to 0.3.…”

Section: Pde Waveletmentioning

confidence: 99%

Despeckleing Prostate Ultrasonograms Using Pde With Wavelet

Ramesh¹,

Manavalan²

2018

IJIVP

View full text Add to dashboard Cite

show abstract

“…Although optical images and SAR images have different scattering characters, many denoising methods for optical images have been extended to speckle suppression. These methods include wavelet method [5, 6], variational method [7–10], partial differential equation (PDE) method [11–15], statistical method [16–19]. Different approaches have different starting points.…”

Section: Introductionmentioning

confidence: 99%