Image Denoising Using Wavelets: Application in Medical Imaging - Advances in Heuristic Signal Processing and Applications - page 306

13.5 Conclusion
In this chapter, denoising of medical images using heuristics based on multiresolu-
tion analysis has been presented, and some practical applications of wavelet domain
denoising in ultrasound and in MRI were revisited.
The presented results demonstrate the usefulness of wavelet denoising for visual
enhancement of images as well as for improving PSNR or SNR. Indeed, wavelet
denoising methods confirmed their interest for noise suppression in ultrasound and
in MRI images.
In the case of echography, the interactive noise reduction scheme, taking into
account prior information as well as local regional statistics, led to a more natural
ultrasound image, in which anatomical features were better kept intact.
In MRI, undecimated discrete wavelet transform as contourlet transform facili-
tates the edge features to be preserved better.
The proposed methods are adapted to medical image denoising since they ac-
count for the preference of the medical expert: a single parameter can be used to
balance the preservation of (expert-dependent) relevant details against the degree of
noise reduction.
These advanced heuristics are of low-complexity, both in their implementation
and execution time. Moreover, they adapt themselves to unknown noise distributions
and to the local spatial image context.
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