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  Mitigating impacts of tissue-heterogeneity and noise bias on MP-PCA denoising for high-quality diffusion MRI

Eichner, C., Paquette, M., Friederici, A. D., & Anwander, A. (2020). Mitigating impacts of tissue-heterogeneity and noise bias on MP-PCA denoising for high-quality diffusion MRI. In Proceedings of the 28th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM).

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-D4A4-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-D4A5-0
Genre: Meeting Abstract

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 Creators:
Eichner, Cornelius1, Author              
Paquette, Michael1, Author              
Friederici, Angela D.1, Author              
Anwander, Alfred1, Author              
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1Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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 Abstract: Advanced diffusion MRI (dMRI) data with high resolution and strong diffusion contrast typically suffer from low SNR levels. Therefore, denoising algorithms such as MP-PCA became an essential part of current dMRI processing pipelines. To overcome challenges related to violations of MP-PCAs assumption of tissue homogeneity in typical dMRI data, we here introduce an informed-MP-PCA (iMP-PCA) algorithm taking local differences in tissue composition into account. Denoising-performance of iMP-PCA was compared to conventional MP-PCA and evaluated on both magnitude and real-valued dMRI data. iMP-PCA was shown to significantly improve denoising-performance, especially at tissue boundaries and in regions of low SNR.

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 Dates: 2020-08-08
 Publication Status: Published online
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Title: Proceedings of the 28th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM)
Source Genre: Proceedings
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Pages: - Volume / Issue: 28 Sequence Number: 4359 Start / End Page: - Identifier: -