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|Title: ||A total variation-undecimated wavelet approach to chest radiograph image enhancement|
|Authors: ||Wilson, Matilda|
Hafron-Acquah, James B.
Aidoo, Anthony Y.
|Keywords: ||chest radiograph|
undecimated wavelet transform
|Issue Date: ||Aug-2019|
|Citation: ||TELKOMNIKA,Vol. 17, No. 4|
|Abstract: ||Most often medical images such as X-Rays have a low dynamic range and many of their
targeted features are difficult to identify. Intensity transformations that improve image quality usually rely
on wavelet denoising and enhancement typically use the technique of thresholding to obtain better
quality medical images. A disadvantage of wavelet thresholding is that even though it adequately
removes noise in an image, it introduces unwanted artifacts into the image near discontinuities.
We utilize a total variation method and an undecimated wavelet image enhancing algorithm for improving
the image quality of chest radiographs. Our approach achieves a high level chest radiograph image
deniosing in lung nodules detection while preserving the important features. Moreover, our method results
in a high image sensitivity that reduces the average number of false positives on a test set of medical data.|
|Description: ||This article is published in TELKOMNIKA and also available at DOI: 10.12928/TELKOMNIKA.v17i4.11911|
|Appears in Collections:||College of Science|
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