Microstructure can have profound effects on the bulk mechanical properties of a material, such as its strength and susceptibility to failure under stress. Several well known methods for imaging microstructure exist, including essentially destructive techniques such as etching and electron back-scattered diffraction, and contact techniques such as the scanning acoustic microscope. SRAS – spatial...

Diffusion MRI is a key in-vivo non invasive imaging capability that can probe the microstructure of the brain. However, its limited resolution requires complex voxelwise generative models of the diffusion. Diffusion Compartment (DC) models divide the voxel into smaller compartments in which diffusion is homogeneous. We present a comprehensive framework for maximum likelihood estimation (MLE) of...

PURPOSE – Diffusion images are known to be corrupted with a non-central chi (NCC)-distributed noise [1]. There has been a number of proposed image denoising methods that account for this particular noise distribution [1,2,3]. However, to the best of our knowledge, no study was performed to assess the influence of the noise model in the context of diffusion model estimation as was suggested in [...

Microstructure imaging combines tailored diffusion MRI acquisition protocols with a mathematical model to give insights into subvoxel tissue features. The is typically fit voxel-by-voxel the image least squares minimisation voxelwise maps of parameters relating microstructural features, such as diffusivities and compartment fractions. However, this fitting approach susceptible noise, which can ...

Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initiali...

Microstructure reconstruction is an important cornerstone to the inverse materials design concept. In this work, a general algorithm developed reconstruct three-dimensional microstructure from given descriptors. Based on two-dimensional (2D) micrographs, allows valuable insight through spatial visualization of and in silico studies structure-property linkages. The formulation ensures computatio...