ArticleIEEE transactions on medical imaging2019
Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramér-Rao Bound Meets Spin Dynamics.
Article in IEEE transactions on medical imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
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85 citing papers in PubMed.
- Self-calibrated BMagnetic resonance in medicine · 2026Article
- Locally Linearized Approximation of RF Pulse Propagators for Faster Simulation of Magnetization Dynamics With Slice Profile Effects in 2D MR Fingerprinting.Magnetic resonance in medicine · 2026Article
- A Magnetic Resonance Fingerprinting Approach for SimultaneousMagnetic resonance in medicine · 2026Article
- Quantitative Assessment of Brain Glucose Metabolism Using Dynamic Glucose-Enhanced Magnetic Resonance Fingerprinting (DGE-MRF).Chemical & biomedical imaging · 2026Article
- Diffusion MRI experimental design optimization for microstructure imaging.Communications biology · 2026Article
- Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint TJournal of magnetic resonance imaging : JMRI · 2026Article
- Optimization of Pulsed Saturation Transfer MR Fingerprinting (ST MRF) Acquisition Using the Cramér-Rao Bound and Sequential Quadratic Programming.Magnetic resonance in medicine · 2026Article
- Physics-informed optimization of saturation-transfer MRI protocols using non-differentiable Bloch models.Physics in medicine and biology · 2026Article
- Multi-contrast generation and quantitative MRI using a transformer-based framework with RF excitation embeddings.Communications biology · 2025Article
- "MR Fingerprinting for Imaging Brain Hemodynamics and Oxygenation".Journal of magnetic resonance imaging : JMRI · 2025Review
- Creatine kinase imaging (CKI) for in vivo whole-brain mapping of creatine kinase reaction kinetics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- 3D multi-phase balanced non-steady-state free precession acquisition for multi-parameter mapping.Magma (New York, N.Y.) · 2025Article
- Quantitative molecular imaging using deep magnetic resonance fingerprinting.Nature protocols · 2025Review
- UltimateSynth: MRI Physics for Pan-Contrast AI.bioRxiv : the preprint server for biology · 2025Article
- Accurate MRF-Based 3D Multi-Channel BNMR in biomedicine · 2025Article
- Three-dimensional high-isotropic-resolution MR fingerprinting optimized for 0.55 T.Magnetic resonance in medicine · 2025Article
- A steady-state MR fingerprinting sequence optimization framework applied to the fast 3D quantification of fat fraction and water T1 in the thigh muscles.Magnetic resonance in medicine · 2025Article
- A flexible MRF approach to improve kinetic rate estimation with bSSFP-based hyperpolarized [1-Magnetic resonance in medicine · 2025Article
- Time-resolved MR fingerprinting for TMagnetic resonance in medicine · 2025Article
- SuperMRF: deep robust reconstruction for highly accelerated magnetic resonance fingerprinting.Quantitative imaging in medicine and surgery · 2025Article
25 more citing papers are in PubMed but not listed here.
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8 authors.
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Abstract
Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which simultaneously acquires multiple MR tissue parameter maps in a single experiment. In this paper, we present an estimation-theoretic framework to perform experiment design for MR fingerprinting. Specifically, we describe a discrete-time dynamic system to model spin dynamics, and derive an estimation-theoretic bound, i.e., the Cramér-Rao bound, to characterize the signal-to-noise ratio (SNR) efficiency of an MR fingerprinting experiment. We then formulate an optimal experiment design problem, which determines a sequence of acquisition parameters to encode MR tissue parameters with the maximal SNR efficiency, while respecting the physical constraints and other constraints from the image decoding/reconstruction process. We evaluate the performance of the proposed approach with numerical simulations, phantom experiments, and in vivo experiments. We demonstrate that the optimized experiments substantially reduce data acquisition time and/or improve parameter estimation. For example, the optimized experiments achieve about a factor of two improvement in the accuracy of T
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