Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images

Park, Minji; Kang, Seong-Hyeon; Kim, Kyuseok; Lee, Youngjin; for the Alzheimer’s Disease Neuroimaging Initiative,

doi:10.3390/app13158803

Open AccessArticle

Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images

by

Minji Park

¹

,

Seong-Hyeon Kang

²,

Kyuseok Kim

^2,*,‡

,

Youngjin Lee

^3,*,‡ and

for the Alzheimer’s Disease Neuroimaging Initiative

^†

¹

Department of Health Science, General Graduate School of Gachon University, 191, Hambakmoe-ro, Yeonsu-gu, Incheon 21936, Republic of Korea

²

Department of Biomedical Engineering, Eulji University, 533, Sanseong-daero, Sujeong-gu, Gyeonggi-do, Seongnam-si 13135, Republic of Korea

³

Department of Radiological Science, Gachon University, 191, Hambakmoe-ro, Yeonsu-gu, Incheon 21936, Republic of Korea

^*

Authors to whom correspondence should be addressed.

^†

Data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (https://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of the ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of the ADNI investigators can be found at: https://adni.loni.usc.edu/wpcontent/uploads/how to apply/ADNI Acknowledgement List.pdf.

^‡

These authors contributed equally to this work.

Appl. Sci. 2023, 13(15), 8803; https://doi.org/10.3390/app13158803

Submission received: 9 July 2023 / Revised: 27 July 2023 / Accepted: 27 July 2023 / Published: 30 July 2023

(This article belongs to the Special Issue Advances in Image and Video Processing: Techniques and Applications)

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Abstract

In this study, we optimized the

σ

-values of a block matching and 3D filtering (BM3D) algorithm to reduce noise in magnetic resonance images. Brain T2-weighted images (T2WIs) were obtained using the BrainWeb simulation program and Rician noise with intensities of 0.05, 0.10, and 0.15. The BM3D algorithm was applied to the optimized BM3D algorithm and compared with conventional noise reduction algorithms using Gaussian, median, and Wiener filters. The clinical feasibility was assessed using real brain T2WIs from the Alzheimer’s Disease Neuroimaging Initiative. Quantitative evaluation was performed using the contrast-to-noise ratio, coefficient of variation, structural similarity index measurement, and root mean square error. The simulation results showed optimal image characteristics and similarity at a σ-value of 0.12, demonstrating superior noise reduction performance. The optimized BM3D algorithm showed the greatest improvement in the clinical study. In conclusion, applying the optimized BM3D algorithm with a σ-value of 0.12 achieved efficient noise reduction.

Keywords: magnetic resonance image; brain T2 weighted image; Rician noise; noise reduction algorithm; optimization of block matching and 3D filtering algorithm; quantitative evaluation of image qualities

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MDPI and ACS Style

Park, M.; Kang, S.-H.; Kim, K.; Lee, Y.; for the Alzheimer’s Disease Neuroimaging Initiative. Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images. Appl. Sci. 2023, 13, 8803. https://doi.org/10.3390/app13158803

AMA Style

Park M, Kang S-H, Kim K, Lee Y, for the Alzheimer’s Disease Neuroimaging Initiative. Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images. Applied Sciences. 2023; 13(15):8803. https://doi.org/10.3390/app13158803

Chicago/Turabian Style

Park, Minji, Seong-Hyeon Kang, Kyuseok Kim, Youngjin Lee, and for the Alzheimer’s Disease Neuroimaging Initiative. 2023. "Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images" Applied Sciences 13, no. 15: 8803. https://doi.org/10.3390/app13158803

APA Style

Park, M., Kang, S.-H., Kim, K., Lee, Y., & for the Alzheimer’s Disease Neuroimaging Initiative. (2023). Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images. Applied Sciences, 13(15), 8803. https://doi.org/10.3390/app13158803

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Simulation and Experimental Studies of Optimization of σ-Value for Block Matching and 3D Filtering Algorithm in Magnetic Resonance Images

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