International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 163 - Issue 7 |
Published: Apr 2017 |
Authors: Matilda Wilson, Anthony Y. Aidoo, Charles H. Acquah, Peter A. Yirenkyi |
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Matilda Wilson, Anthony Y. Aidoo, Charles H. Acquah, Peter A. Yirenkyi . Chest Radiograph Image Enhancement: A Total Variation Approach. International Journal of Computer Applications. 163, 7 (Apr 2017), 1-7. DOI=10.5120/ijca2017913466
@article{ 10.5120/ijca2017913466, author = { Matilda Wilson,Anthony Y. Aidoo,Charles H. Acquah,Peter A. Yirenkyi }, title = { Chest Radiograph Image Enhancement: A Total Variation Approach }, journal = { International Journal of Computer Applications }, year = { 2017 }, volume = { 163 }, number = { 7 }, pages = { 1-7 }, doi = { 10.5120/ijca2017913466 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A Matilda Wilson %A Anthony Y. Aidoo %A Charles H. Acquah %A Peter A. Yirenkyi %T Chest Radiograph Image Enhancement: A Total Variation Approach%T %J International Journal of Computer Applications %V 163 %N 7 %P 1-7 %R 10.5120/ijca2017913466 %I Foundation of Computer Science (FCS), NY, USA
Wavelet denoising of medical images relies on the technique of thresholding. A disadvantage of this method is that even though it adequately removes noise in an image, it introduces unwanted artifacts into the image near discontinuities due to Gibbs phenomenon. A total variation method for enhancing chest radiographs is implemented. The approach focuses on lung nodules detection using chest radiographs (CRs) and the method achieves high image sensitivity and could reduce the average number of false positives radiologists encounter.