ArticleImaging neuroscience (Cambridge, Mass.)2025
Maximum-entropy and subspace methods for high-resolution relaxation-diffusion distribution estimation.
Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Informed Dictionary-Guided Monte Carlo Inversion for Robust and Reproducible Multidimensional MRI.Magnetic resonance in medicine · 2026Article
- Age-dependent diffusion-relaxation coupling in the basal ganglia: Implications for iron deposition and microstructural dynamics.Imaging neuroscience (Cambridge, Mass.)Article
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Abstract
Relaxation-diffusion distribution characterizes tissue microstructure using multi-contrast MRI data without using a multi-compartment model. This work applies and generalizes two nonlinear spectral estimation algorithms to compute relaxation-diffusion distributions and compares their performances with the standard linear inverse method. The first algorithm employs maximum entropy (MaxEnt) estimation, extending previous methods by incorporating measurement noise for improved robustness. The second algorithm is based on the MUltiple SIgnal Classification (MUSIC) subspace spectral estimation technique, enabling pseudo-spectral estimation of multi-exponential signals sampled on regular grids without solving optimization problems. Both methods were compared against the basis representation technique and the nonnegative least squares (NNLS) method using synthetic and
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