Open AccessProceedings Article
Modified Anisotropic Diffusion filtering algorithm for MRI
Aditya Srivastava,Vikrant Bhateja,Harshit Tiwari +2 more
- 11 Mar 2015
- pp 1885-1890
11
TL;DR: The proposed modified Anisotropic Diffusion algorithm aimed to improve the estimation of the diffusion constant to facilitate better edge detection and preservation of details has shown stable value of evaluation parameters at higher noise variances.
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Abstract: During the acquisition process of Magnetic Resonance Imaging (MRI), irregular bias is imposed in the intensity values of the pixels. These biases follow the Gaussian Noise distribution model and act as a constraint to the effective medical diagnosis. The conventional Anisotropic Diffusion (AD) approach is limited to preserve the structural integrity of MRI at only low noise levels. This paper proposes a modified AD algorithm aimed to improve the estimation of the diffusion constant to facilitate better edge detection and preservation of details. The proposed algorithm operates on the decomposed mask images of MRI by incorporating the domain filtering principle of the Bilateral filter(prior to the estimation of diffusion constant). Simulation trials have been conducted at different Gaussian noise variances and performance has been evaluated on the basis of Peak Signal-Noise Ratio (PSNR) and Structural Similarity (SSIM). The proposed algorithm has shown stable value of evaluation parameters at higher noise variances. Also, the preservation of details has improved as compared to the conventional AD approach.
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References
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
Bilateral filtering for gray and color images
Carlo Tomasi,Roberto Manduchi +1 more
- 04 Jan 1998
TL;DR: In contrast with filters that operate on the three bands of a color image separately, a bilateral filter can enforce the perceptual metric underlying the CIE-Lab color space, and smooth colors and preserve edges in a way that is tuned to human perception.
Image selective smoothing and edge detection by nonlinear diffusion. II
TL;DR: In this article, a new version of the Perona and Malik theory for edge detection and image restoration is proposed, which keeps all the improvements of the original model and avoids its drawbacks.
Robust anisotropic diffusion
TL;DR: It is shown that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image and the connection to the error norm and influence function in the robust estimation framework leads to a new "edge-stopping" function based on Tukey's biweight robust estimator that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion.
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Nonlinear anisotropic filtering of MRI data
TL;DR: In contrast to acquisition-based noise reduction methods a postprocess based on anisotropic diffusion is proposed, which overcomes the major drawbacks of conventional filter methods, namely the blurring of object boundaries and the suppression of fine structural details.
1.3K