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Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Enhancement of radiographic images in patients with lung nodules
Maher I Rajab1, Ayman A Eskandar1
1Department of Computer Engineering, College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia Department of Radiology, College of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Abstract:
Detection of lung nodules in a chest Radiograph is very difficult due to sensitivity to noise, lighting, and similar disturbances of the blood vessels and trachea. Therefore, such images need to be carefully examined to identify and characterize lung lesions. However, human interpretations are usually contradictory and may cause confusion. Current works propose an image processing technique based on frequency domain processing to clarify X-ray radiographic images taken in patients with a variety of lung lesions. The Picture Archiving and Communication Systems workstation allows transferring radiographic data from DICOM into JPEG image formats. In the preprocessing phase, the lung nodules are identified by an experienced chest radiologist and used for extracting regions of interest. Subsequently, low-pass followed by emphasis high-pass frequency filters are applied to enhance the images with appropriate cut-off frequencies. It has been found that high-frequency domain image filtering enhances the morphological features of lung masses. Enhanced images are then visually arbitrated by an expert radiologist. We found that the characteristics of lung lesions are easily identified after this process.
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