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Frederik Bernd Laun

Researcher at University of Erlangen-Nuremberg

Publications -  131
Citations -  3970

Frederik Bernd Laun is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Diffusion (business) & Medicine. The author has an hindex of 28, co-authored 117 publications receiving 3275 citations. Previous affiliations of Frederik Bernd Laun include German Cancer Research Center & Atos.

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Methodological considerations on tract-based spatial statistics (TBSS).

TL;DR: Specific assumptions of TBSS that may not be satisfied under typical conditions are identified and it is demonstrated that the existence of such violations can severely affect the reliability of T BSS results.
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Toward an optimal distribution of b values for intravoxel incoherent motion imaging

TL;DR: This work determined optimal b value distributions for the three parameter fit are determined using Monte-Carlo simulations for the measurement of a low, medium and high IVIM perfusion regime.
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Sodium MRI using a density-adapted 3D radial acquisition technique

TL;DR: It is shown that the density‐adapted three‐dimensional radial projection reconstruction pulse sequence allows higher resolutions and is more robust in the presence of field inhomogeneities, and benefits for low SNR applications, when compared to conventional three‐ dimensional projection reconstruction sequences.
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An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen.

TL;DR: A vascular contribution to the diffusion weighted imaging measurement at low b values is verified and support the Intra Voxel Incoherent Motion‐theory.
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Differentiation of pancreas carcinoma from healthy pancreatic tissue using multiple b-values: comparison of apparent diffusion coefficient and intravoxel incoherent motion derived parameters.

TL;DR: The f value proved to be the best parameter for the differentiation between healthy pancreas and pancreatic cancer using the IVIM-approach, and showed more than a 10-fold higher significance level in distinguishing cancerous from normal tissue when compared with the ADCtot value.