Isa Sadigli

Master's Student

Thesis Topic: Q-Space Trajectory Imaging: Comparing QTI Fit Packages and Pre-processing Implementations.
Supervisors: Annika Hofmann, Prof Dr. Florian Knoll

Description

My thesis evaluates and compares different implementations for fitting Q-Space Trajectory Imaging (QTI) metrics in diffusion MRI, with a focus on pre-processing for EPI distortions and motion correction (e.g., topup/elastix) and the impact of these steps on QTI measures. I compare existing toolchains and assemble a reproducible pipeline for motion correction and QTI fitting, assessing accuracy and artefact suppression across datasets.

References

[1] Westin CF, Knutsson H, Pasternak O, et al. Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. Neuroimage. 2016;135:345-362. doi:10.1016/j.neuroimage.2016.02.039.

[2] Herberthson M, Boito D, Haije TD, Feragen A, Westin CF, Özarslan E. Q-space trajectory imaging with positivity constraints (QTI+). Neuroimage. 2021;238:118198. doi:10.1016/j.neuroimage.2021.118198.

[3] Nilsson M, Szczepankiewicz F, Lampinen B, et al. An open-source framework for analysis of multidimensional diffusion MRI data implemented in MATLAB. In: Presented at: 26th annual meeting of the international society for magnetic resonance in medicine (ISMRM); June 16-21, 2018; Paris, France. International Society for Magnetic Resonance in Medicine. 2018.