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Improving Image Quality in Medical Images Using a Combined Method of Undecimated Wavelet Transform and Wavelet Coefficient Mapping
Author(s) -
DuYih Tsai,
Eri Matsuyama,
HsianMin Chen
Publication year - 2013
Publication title -
international journal of biomedical imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.626
H-Index - 41
eISSN - 1687-4196
pISSN - 1687-4188
DOI - 10.1155/2013/797924
Subject(s) - artificial intelligence , computer science , preprocessor , wavelet , pattern recognition (psychology) , image quality , computer vision , noise (video) , wavelet transform , discrete wavelet transform , image (mathematics)
We propose a method for improving image quality in medical images by using a wavelet-based approach. The proposed method integrates two components: image denoising and image enhancement. In the first component, a modified undecimated discrete wavelet transform is used to eliminate the noise. In the second component, a wavelet coefficient mapping function is applied to enhance the contrast of denoised images obtained from the first component. This methodology can be used not only as a means for improving visual quality of medical images but also as a preprocessing module for computer-aided detection/diagnosis systems to improve the performance of screening and detecting regions of interest in images. To confirm its superiority over existing state-of-the-art methods, the proposed method is experimentally evaluated via 30 mammograms and 20 chest radiographs. It is demonstrated that the proposed method can further improve the image quality of mammograms and chest radiographs, as compared to two other methods in the literature. These results reveal the effectiveness and superiority of the proposed method.

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