Applying positivity constraints to q-space trajectory imaging: The QTI+ implementation

SoftwareX

Magnus Herberthson¹  Tom Dela Haije²  Deneb Boito³  Evren Özarslan⁴ 

[1] Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden;Corresponding author at: Department of Biomedical Engineering, Linköping University, Linköping, Sweden.;Department of Biomedical Engineering, Linköping University, Linköping, Sweden;Department of Mathematics, Linköping University, Linköping, Sweden;

关键词: Diffusion MRI;    QTI;    Constrained estimation;    Microscopic anisotropy;   

DOI  :  

来源: DOAJ

【 摘 要 】

Diffusion MRI is a powerful technique sensitive to the microstructure of heterogeneous media. By relating the dMRI signal obtained via general gradient waveforms to the moments of an underlying diffusion tensor distribution, q-space trajectory imaging (QTI) provides several quantities indicative of the structural composition of the medium. Substantial improvements in the reliability of the produced estimates has been achieved via incorporating necessary positivity constraints in the estimation by employing Semidefinite Programming. Here we present the Matlab code implementing said constraints, provide a simple example showing the main functionalities of the package, and point to resources within the package that can be used to reproduce results recently published with this software. The block-based structure of our implementation allows the selection of steps to be performed, and facilitates the incorporation of new constraints in future releases.

【 授权许可】

Unknown