Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM)
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arXiv
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| Format: | Preprint |
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2024
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| author | Doniza, Liad Lee, Mitchel Katzir, Tamar Blumenfeld Artzi, Moran Bashat, Dafna Ben Radunsky, Dvir Shmueli, Karin Ben-Eliezer, Noam |
| author_facet | Doniza, Liad Lee, Mitchel Katzir, Tamar Blumenfeld Artzi, Moran Bashat, Dafna Ben Radunsky, Dvir Shmueli, Karin Ben-Eliezer, Noam |
| contents | Quantitative Susceptibility Mapping (QSM) is a technique for measuring magnetic susceptibility of tissues, aiding in the detection of pathologies like traumatic brain injury and multiple sclerosis by analyzing variations in substances such as iron and calcium. Despite its clinical value, achieving high-resolution QSM (voxel sizes < 1 mm3) reduces signal-to-noise ratio (SNR), compromising diagnostic quality. To mitigate this, we applied the Marchenko-Pastur Principal Component Analysis (MP-PCA) denoising technique on T2* weighted data, to enhance the quality of R2*, T2*, and QSM maps. Denoising was tested on a numerical phantom, healthy subjects, and patients with brain metastases and sickle cell disease, demonstrating effective and robust improvements across different scan settings. Further analysis examined noise propagation in R2* and T2* values, revealing lower noise-related variations in R2* values compared to T2* values which tended to be overestimated due to noise. Reduced variability was observed in QSM values post denoising, demonstrating MP-PCA's potential to improve the |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_19309 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM) Doniza, Liad Lee, Mitchel Katzir, Tamar Blumenfeld Artzi, Moran Bashat, Dafna Ben Radunsky, Dvir Shmueli, Karin Ben-Eliezer, Noam Quantitative Methods Quantitative Susceptibility Mapping (QSM) is a technique for measuring magnetic susceptibility of tissues, aiding in the detection of pathologies like traumatic brain injury and multiple sclerosis by analyzing variations in substances such as iron and calcium. Despite its clinical value, achieving high-resolution QSM (voxel sizes < 1 mm3) reduces signal-to-noise ratio (SNR), compromising diagnostic quality. To mitigate this, we applied the Marchenko-Pastur Principal Component Analysis (MP-PCA) denoising technique on T2* weighted data, to enhance the quality of R2*, T2*, and QSM maps. Denoising was tested on a numerical phantom, healthy subjects, and patients with brain metastases and sickle cell disease, demonstrating effective and robust improvements across different scan settings. Further analysis examined noise propagation in R2* and T2* values, revealing lower noise-related variations in R2* values compared to T2* values which tended to be overestimated due to noise. Reduced variability was observed in QSM values post denoising, demonstrating MP-PCA's potential to improve the |
| title | Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM) |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2404.19309 |