Some of the major aspects of computer vision systems in medical imaging involving wavelet analysis are reviewed in this chapter. Initially, key concepts of wavelet decomposition theory are defined, focusing on the overcomplete discrete dyadic wavelet transform, suitable for image quality preserving analysis. Next, basic principles underlying methods such as (i) wavelet coefficient manipulations involved in image denoising and enhancement, and (ii) wavelet feature extraction involved in image segmentation and classification tasks are highlighted. Finally, application examples corresponding to the above mentioned methods are provided for various medical imaging modalities with emphasis on mammographic imaging.
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