摘要：Noise suppression in medical images is a particularly delicate and difficult task. A trade-off between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Image processing specialists usually lack the biomedical expertise to judge the diagnostic relevance of the De-noising results. For example, in ultrasound images, speckle noise may contain information useful to medical experts the use of speckled texture for a diagnosis was discussed in. Also biomedical images show extreme variability and it is necessary to operate on a case by case basis. This motivates the construction of robust and Efficient denoising methods that are applicable to various circumstances, rather than being optimal under very specific conditions. In this paper, we propose one robust method that adapts itself to various types of image noise as well as to the preference of the medical expert: a single parameter can be used to balance the preservation of relevant details against the degree of noise reduction. The proposed algorithm is simple to implement and fast. We demonstrate its usefulness for denoising and enhancement of the CT, Ultrasound and Magnetic Resonance images.
