Research Article
Open Access
Fuzzy Logic-Based Mixed Noise Reduction in Ultrasound Images
1
Department of Electrical and Electronic Engineering, Gopalganj Science and Technology University, Gopalganj 8105, Bangladesh
2
Department of Electrical and Electronic Engineering, University of Information Technology & Sciences, Dhaka 1212, Bangladesh
* Corresponding Author:
Priyankar Biswas,
[email protected]
Volume 1, Issue 4
2025
Received: 30 October 2025
Accepted: 06 December 2025
Published: 15 December 2025
Article Information
Published in
ICCK Journal of Image Analysis and Processing
Volume/Issue
Volume 1, Issue 4, 2025
Pages
184-195
Abstract
Ultrasound (US) imaging is widely employed in medical diagnostics due to its non-invasive nature and real-time imaging ability. The existence of mixed noise, consisting of Gaussian and speckle noise, significantly impairs image quality, hindering accurate diagnosis. This study introduces an advanced fuzzy logic-based technique for noise reduction to enhance US image quality while preserving essential structural information. The proposed approach utilizes a modified Gaussian membership function to improve the filtering process, ensuring adaptive noise reduction across varying noise levels. The system is evaluated on synthetic and clinical US images using diverse image quality assessment metrics. The experimental results demonstrate that the proposed method exceeds existing top denoising techniques in terms of noise reduction, edge preservation, and image clarity. This work presents a systematic and effective approach for improving US image quality, hence augmenting medical analysis and diagnosis.
Graphical Abstract
Keywords
ultrasound imaging
speckle noise
gaussian noise
fuzzy filtering
restored image
Data Availability Statement
Data will be made available on request.
Funding
This work was supported without any funding.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
References
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APA Style
Biswas, P., Islam, A. T. M. S., & Mondal, K. (2025). Fuzzy Logic-Based Mixed Noise Reduction in Ultrasound Images. ICCK Journal of Image Analysis and Processing, 1(4), 184–195. https://doi.org/10.62762/JIAP.2025.159583
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TY - JOUR AU - Biswas, Priyankar AU - Islam, A. T. M. Saiful AU - Mondal, Krishnapada PY - 2025 DA - 2025/12/15 TI - Fuzzy Logic-Based Mixed Noise Reduction in Ultrasound Images JO - ICCK Journal of Image Analysis and Processing T2 - ICCK Journal of Image Analysis and Processing JF - ICCK Journal of Image Analysis and Processing VL - 1 IS - 4 SP - 184 EP - 195 DO - 10.62762/JIAP.2025.159583 UR - https://www.icck.org/article/abs/JIAP.2025.159583 KW - ultrasound imaging KW - speckle noise KW - gaussian noise KW - fuzzy filtering KW - restored image AB - Ultrasound (US) imaging is widely employed in medical diagnostics due to its non-invasive nature and real-time imaging ability. The existence of mixed noise, consisting of Gaussian and speckle noise, significantly impairs image quality, hindering accurate diagnosis. This study introduces an advanced fuzzy logic-based technique for noise reduction to enhance US image quality while preserving essential structural information. The proposed approach utilizes a modified Gaussian membership function to improve the filtering process, ensuring adaptive noise reduction across varying noise levels. The system is evaluated on synthetic and clinical US images using diverse image quality assessment metrics. The experimental results demonstrate that the proposed method exceeds existing top denoising techniques in terms of noise reduction, edge preservation, and image clarity. This work presents a systematic and effective approach for improving US image quality, hence augmenting medical analysis and diagnosis. SN - 3068-6679 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Biswas2025Fuzzy,
author = {Priyankar Biswas and A. T. M. Saiful Islam and Krishnapada Mondal},
title = {Fuzzy Logic-Based Mixed Noise Reduction in Ultrasound Images},
journal = {ICCK Journal of Image Analysis and Processing},
year = {2025},
volume = {1},
number = {4},
pages = {184-195},
doi = {10.62762/JIAP.2025.159583},
url = {https://www.icck.org/article/abs/JIAP.2025.159583},
abstract = {Ultrasound (US) imaging is widely employed in medical diagnostics due to its non-invasive nature and real-time imaging ability. The existence of mixed noise, consisting of Gaussian and speckle noise, significantly impairs image quality, hindering accurate diagnosis. This study introduces an advanced fuzzy logic-based technique for noise reduction to enhance US image quality while preserving essential structural information. The proposed approach utilizes a modified Gaussian membership function to improve the filtering process, ensuring adaptive noise reduction across varying noise levels. The system is evaluated on synthetic and clinical US images using diverse image quality assessment metrics. The experimental results demonstrate that the proposed method exceeds existing top denoising techniques in terms of noise reduction, edge preservation, and image clarity. This work presents a systematic and effective approach for improving US image quality, hence augmenting medical analysis and diagnosis.},
keywords = {ultrasound imaging, speckle noise, gaussian noise, fuzzy filtering, restored image},
issn = {3068-6679},
publisher = {Institute of Central Computation and Knowledge}
}
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