Estimation of multiple components and parameters for quantitative MRI

Magnetic Resonance Imaging (MRI) is a flexible medical imaging technique that facilitates measurement of a wide range of contrasts particularly in soft tissue (e.g. brain and heart). Conventionally, qualitative images are acquired in which certain physical tissue properties are emphasized such as the transverse and longitudinal relaxation times....

White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis

T₂-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We...

Accuracy and repeatability of joint sparsity multi-component estimation in MR Fingerprinting

MR fingerprinting (MRF) is a promising method for quantitative characterization of tissues. Often, voxel-wise measurements are made, assuming a single tissue-type per voxel. Alternatively, the Sparsity Promoting Iterative Joint Non-negative least squares Multi-Component MRF method (SPIJN-MRF) facilitates tissue parameter estimation for...

Fast multi-component analysis using a joint sparsity constraint for MR fingerprinting

<br/>Purpose<br/><br/>To develop an efficient algorithm for multi‐component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties.<br/>Methods<br/><br/>Different tissues or components within a voxel are potentially separable in MRF because of...