Introduction:
Imaging methods are progressing in a rapidly manner, but the problem which we, as the health providers always encounter with is the expensive costs of different devices and our limited budget to provide them.
Shiraz E-Medical Journal
Imaging methods are progressing in a rapidly manner, but the problem which we, as the health providers always encounter with is the expensive costs of different devices and our limited budget to provide them.
The aim of this study is to evaluate the usefulness of Histogram Equalization (HE) and Unsharp Mask (UM) on the conventional CXR images.
In Urmia University of Medical Sciences, we designed a windows-based computer program that contains histogram equalization (HE), unsharp mask (UM) and com-bination of HE and UM algorithms with adjusted parameters to process conventional chest x-ray (CXR) images. Two series of CXR images including 49 images without major pulmonary disorder and 45 images with pulmonary parenchymal disorders were selected. After convert-ing them to digital format, images were processed with HE, UM and combination of HE and UM techniques. In each series, original and processed images were saved in 4 databases. Two board-certified general radiologists (with 6 and 5 years experience) analyzed images. Saved images were displayed to radiologists randomly and separately. Quality of each image was saved as a scale from 1 (very low quality) to 5 (excellent). We used a variance-based statistical technique to analyze quality.
To compare the quality of each algorithm (GHE, UM and combina-tion of GHE and UM), a variance-based statistical analysis was done.
In the first series images, HE and combination of HE and UM algorithms increased quality of images, but UM technique was not suitable, solely. Also, all three techniques in-creased quality of second series images.
The use of digital image processing algorithms such as HE or UM on conven-tional CXR images can increase quality of images.
© 2011, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.
Li X, Luo S, Chen S, Wang D, Tan Y. Contrast-Enhanced Chest Computed Tomography (CT) Scan with Low Radiation and Total Iodine Dose for Lung Cancer Detection Using Adaptive Statistical Iterative Reconstruction. I J Radiol. 2022;19(4):e126572. doi: https://doi.org/10.5812/iranjradiol-126572
Aziz A, Khan A, Nam Y, Cho Y. Enhanced Diagnosis of Chest X-Ray Using Hybrid Deep Learning Models and Feature Selection Techniques. I J Radiol. 2025;22(3):e163605. doi: https://doi.org/10.5812/iranjradiol-163605
Seong Kim M, Lee J, Geun Kim S, Cheol Kweon D. Comparison of Radiation Dose and Image Quality with Various Computed-Tomography Scout Views: The Angular Modulation Technique Based on Information Calculated from Scout Views. I J Radiol. 2017;14(1):e13477. doi: https://doi.org/10.5812/iranjradiol.35606
Belash Abadi S, Davoodi M. Comparison of Image Quality of Low Voltage 64-Slice Multidetector CT Angiography (80 Kilovoltage) With Standard Condition (100 Kilovoltage) in Patients Suspected of Pulmonary Emboli. I J Radiol. 2014;11(30th Iranian Congress of Radiology):e21270. doi: https://doi.org/10.5812/iranjradiol.21270
Mahmoudabadi A, Keshtkar M, Sadeghi Moghadam M. Challenges of Irradiation on Extrathoracic and Non-thoracic Organs in Portable Neonatal Chest Radiography: Do We Need Mandatory Protective Rules?. Inn J Pediatr. 2021;31(2):e107258. doi: https://doi.org/10.5812/ijp.107258
Ordering Reprints
Articles are published under the Creative Commons license stated on each article. No permission or royalty fee is required for uses permitted by that license. CCC handles optional bulk and customized reprint orders. Any quotation covers production and delivery services only, not copyright permission. > Request Reprints from CCC
Author(s):