Volume 43, Issue 4 (12-2019)
Research in Medicine 2019, 43(4): 192-197 |
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Ghaempanah H, Deevband M R, Asgharzadeh Alvar A, Najafi M. Wavelet-based Enhancement of Electronic Portal Images. Research in Medicine 2019; 43 (4) :192-197
URL: http://pejouhesh.sbmu.ac.ir/article-1-1943-en.html
URL: http://pejouhesh.sbmu.ac.ir/article-1-1943-en.html
School of Medicine Shahid Beheshti University of Medical Sciences , mdeevband@sbmu.ac.ir
Abstract: (3118 Views)
Background: In order to accurately deliver a prescribed dose to the treatment target volume, electronic portal images are widely used. However, the use of megavoltage beam leads to low tissue contrast. The inherently poor quality of portal images makes it difficult to interpret them. In this regard, a wavelet-based processing is performed to improve their visual quality.
Materials and methods: In the present experimental study, 150 pelvis portal images of 30 patients were obtained. To prepare the images for implementation of the enhancement algorithm, the pre-processing was performed in terms of noise reduction and intensity adjustment. Then, the local details enhancement and sharpening the bone edges were done on the approximation and detail subbands of the wavelet decomposition. Afterwards, in the case of non-periodic pattern and non-uniform background in the noisy images, two quality measures of images, including Edge Content (EC) and Measure of Enhancement (EME), were evaluated. Finally, the given results were analyzed using the statistical paired t-test.
Findings: The higher values of these two measures proved the superior quality of processed images relative to the original one (ECoriginal=0.0046±0.008, ECenhanced=0.0790±0.001, and EMEoriginal=0.3950±0.180, EMEenhanced=13.875±1.227).
Conclusion: A wavelet-based enhancement algorithm for portal image enhancement can be an effective approach to reveal more anatomical information, which results in more precise setup verification. In future studies, the evaluation of this algorithm is recommended for the enhancement of the other organs portal images.
Materials and methods: In the present experimental study, 150 pelvis portal images of 30 patients were obtained. To prepare the images for implementation of the enhancement algorithm, the pre-processing was performed in terms of noise reduction and intensity adjustment. Then, the local details enhancement and sharpening the bone edges were done on the approximation and detail subbands of the wavelet decomposition. Afterwards, in the case of non-periodic pattern and non-uniform background in the noisy images, two quality measures of images, including Edge Content (EC) and Measure of Enhancement (EME), were evaluated. Finally, the given results were analyzed using the statistical paired t-test.
Findings: The higher values of these two measures proved the superior quality of processed images relative to the original one (ECoriginal=0.0046±0.008, ECenhanced=0.0790±0.001, and EMEoriginal=0.3950±0.180, EMEenhanced=13.875±1.227).
Conclusion: A wavelet-based enhancement algorithm for portal image enhancement can be an effective approach to reveal more anatomical information, which results in more precise setup verification. In future studies, the evaluation of this algorithm is recommended for the enhancement of the other organs portal images.
Keywords: Radiation therapy, Electronic portal image, Digital Image Processing, Wavelet, Image quality
Type of Study: Original |
Subject:
Physics and Medical Engineering
Received: 2018/10/28 | Accepted: 2019/06/3 | Published: 2019/12/21
Received: 2018/10/28 | Accepted: 2019/06/3 | Published: 2019/12/21
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