Speckle Noise Reduction via Homomorphic Elliptical Threshold Rotations in the Complex Wavelet Domain

Electrical & Computer Engineering;signal processing;speckle noise;wavelet;ultrasound

Ng, Edmund

University of Waterloo

关键词: Electrical & Computer Engineering;    signal processing;    speckle noise;    wavelet;    ultrasound;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/812/1/ehng2005.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Many clinicians regard speckle noise as an undesirable artifact in ultrasound images masking the underlying pathology within a patient. Speckle noise is a random interference pattern formed by coherent radiation in a medium containing many sub-resolution scatterers. Speckle has a negative impact on ultrasound images as the texture does not reflect the local echogenicity of the underlying scatterers. Studies have shown that the presence of speckle noise can reduce a physician;;s ability to detect lesions by a factor of eight.Without speckle, small high-contrast targets, low contrast objects, and image texture can be deduced quite readily.

Speckle filtering of medical ultrasound images represents a critical pre-processing step, providing clinicians with enhanced diagnostic ability.Efficient speckle noise removal algorithms may also find applications in real time surgical guidance assemblies. However, it is vital that regions of interests are not compromised during speckle removal. This research pertains to the reduction of speckle noise in ultrasound images while attempting to retain clinical regions of interest.

Recently, the advance of wavelet theory has lead to many applications in noise reduction and compression.Upon investigation of these two divergent fields, it was found that the speckle noise tends to rotate an image;;s homomorphic complex-wavelet coefficients. This work proposes a new speckle reduction filter involving a counter-rotation of these complex-wavelet coefficients to mitigate the presence of speckle noise. Simulations suggest the proposed denoising technique offers superior visual quality, though its signal-to-mean-square-error ratio (S/MSE) is numerically comparable to adaptive frost and kuan filtering.

This research improves the quality of ultrasound medical images, leading to improved diagnosis for one of the most popular and cost effective imaging modalities used in clinical medicine.