Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM) Article Swipe
Liad Doniza
,
Mitchel Lee
,
Tamar Blumenfeld Katzir
,
Moran Artzi
,
Dafna Ben Bashat
,
Dvir Radunsky
,
Karin Shmueli
,
Noam Ben‐Eliezer
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.19309
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.19309
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
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2404.19309
- https://arxiv.org/pdf/2404.19309
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396600583
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396600583Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2404.19309Digital Object Identifier
- Title
-
Noise propagation and MP-PCA image denoising for high-resolution quantitative T2* and magnetic susceptibility mapping (QSM)Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-30Full publication date if available
- Authors
-
Liad Doniza, Mitchel Lee, Tamar Blumenfeld Katzir, Moran Artzi, Dafna Ben Bashat, Dvir Radunsky, Karin Shmueli, Noam Ben‐EliezerList of authors in order
- Landing page
-
https://arxiv.org/abs/2404.19309Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2404.19309Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2404.19309Direct OA link when available
- Concepts
-
Quantitative susceptibility mapping, Noise reduction, Image denoising, Noise (video), Resolution (logic), Pattern recognition (psychology), Artificial intelligence, High resolution, Computer science, Image (mathematics), Medicine, Magnetic resonance imaging, Radiology, Geography, Remote sensingTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.measuring | 8 |
| abstract_inverted_index.numerical | 87 |
| abstract_inverted_index.potential | 149 |
| abstract_inverted_index.revealing | 119 |
| abstract_inverted_index.sclerosis | 25 |
| abstract_inverted_index.settings. | 108 |
| abstract_inverted_index.subjects, | 90 |
| abstract_inverted_index.technique | 6, 67 |
| abstract_inverted_index.traumatic | 20 |
| abstract_inverted_index.denoising, | 146 |
| abstract_inverted_index.diagnostic | 53 |
| abstract_inverted_index.metastases | 95 |
| abstract_inverted_index.substances | 30 |
| abstract_inverted_index.variations | 28, 122 |
| abstract_inverted_index.pathologies | 18 |
| abstract_inverted_index.propagation | 113 |
| abstract_inverted_index.variability | 139 |
| abstract_inverted_index.Quantitative | 0 |
| abstract_inverted_index.compromising | 52 |
| abstract_inverted_index.improvements | 104 |
| abstract_inverted_index.demonstrating | 100, 147 |
| abstract_inverted_index.noise-related | 121 |
| abstract_inverted_index.overestimated | 134 |
| abstract_inverted_index.Susceptibility | 1 |
| abstract_inverted_index.susceptibility | 10 |
| abstract_inverted_index.high-resolution | 41 |
| abstract_inverted_index.signal-to-noise | 49 |
| abstract_inverted_index.Marchenko-Pastur | 61 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |