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A Repeated Median Filtering Method for Denoising Mammogram Images
Open accessAbstract
In the medical field, mammogram analysis is one of the most important breast cancer detection procedures and early diagnosis. During the image acquisition process of mammograms, the acquired images may be contained some noises due to the change of illumination and sensor error. Hence, it is necessary to remove these noises without affecting the edges and fine details, achieving an effective diagnosis of beast images. In this work, a repeated median filtering method is proposed for denoising digital mammogram images. A number of experiments are conducted on a dataset of different mammogram images to evaluate the proposed method using a set of image quality metrics. Experimental results are reported by computing the image quality metrics between the original clean images and denoised images that are corrupted by different levels of simulated speckle noise as well as salt and paper noise. Evaluation quality metrics showed that the repeated median filter method achieves a higher result than the related traditional median filter method.
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“Evaluation quality metrics show that the repeated median filter method achieves higher results than the related traditional median filter method[15].”
From Digital Image Noise Reduction Application with Mean And Median Filter Method (2021) · cites this paper as [15]
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Gumaei, A., Hassan, M. M., Hassan, M. R., Alelaiwi, A., & Fortino, G. (2019) · IEEE Access · doi:10.1109/access.2019.2904145 · Cited by 484 · cited 2×
“Therefore, MF is widely used in digital image processing [3].”
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Digital Image Noise Reduction Application with Mean And Median Filter Method
Rangkuti, R. F. (2021) · Instal : Jurnal Komputer · doi:10.54209/jurnalkomputer.v12i01.12
“Evaluation quality metrics show that the repeated median filter method achieves higher results than the related traditional median filter method[15].”
Method
Metadata
- Authors
- AlSalman, H.
- Affiliations
- King Saud University (SA)
- Corresponding author
- AlSalman, Hussain
- ORCID
- AlSalman, Hussain
- Venue
- International Journal of Advanced Computer Science and Applications
- Published
- 2020
- Volume
- 11
- Issue
- 11
- ISSN
- 2156-5570 (ISSN-L)
- 2158-107X
- OpenAlex
- W3110866549
- Cited by
- 6
- References
- 1
- Citations by year
- 2025: 1 · 2024: 4 · 2021: 1
- FWCI
- 0.10
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Advanced Computer Science and Applications (publishedVersion, cc-by)
- International Journal of Advanced Computer Science and Applications (submittedVersion, cc-by)
- Funders
- King Saud University
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Digital Radiography and Breast Imaging
- Keywords
- median filter, speckle noise, salt and pepper noise, breast cancer detection, edge preservation, image quality metrics
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