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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12959

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
image enhancement
total variation
undecimated wavelet transform
Issue Date: Aug-2019
Publisher: TELKOMNIKA
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
URI: 10.12928/TELKOMNIKA.v17i4.11911
http://hdl.handle.net/123456789/12959
Appears in Collections:College of Science

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