arXiv subjects

Hongli Fan

Publications and source records attributed to Hongli Fan.

7 recordsLinked to original sources

arXiv2026

MR-Compass: Inertial Navigation-Driven Motion Correction for Brain MRI

Inertial sensors can track object kinematics, however, unbounded drift from integrating noisy signals makes them impractical for MRI motion correction at millimeter resolution and minute-long scans. We introduce MR-Compass, which exploits the MRI system's static magnetic and gravitational fields to estimate 3-DOF orientation at 2 kHz directly, without integration, eliminating random-walk. The remaining 3-DOF translation is recovered via phase correlation from the MRI data. We experimentally validate the efficacy of the method retrospectively using a 3D radial koosh-ball sequence and prospectively using 2D EPI fMRI during large volunteer motions. MR-Compass followed by phase-correlation achieved a mean accuracy of 0.6$^o$ and 0.4 pixels across all experiments. Image quality improved when motion correction was applied in all volunteer scans for both retrospective and prospective correction cases. MR-Compass was effective in measuring head motion in the MRI scanner with high accuracy at unprecedented sample rates, and enabled both retrospective and prospective reconstruction to improve image quality by aligning the k-space data appropriately and by reducing the motion related artifacts.

eess.IV↗

arXiv2025

Enhanced numerical models for two-component fluid flow in multiscale porous structures

Multi-component fluid flow simulations in multi-scale porous structures often involve regions that are under-resolved at practical computational resolutions. Accurately capturing the contributions from these unresolved regions is critical. Previous studies proposed a model to account for viscous and capillary forces in under-resolved regions, showing permeability, capillary pressure, and relative permeability comparable to fully resolved high-resolution cases. In this study, we extend the model to handle diverse structures and capture detailed fluid behavior. We introduce controllable surface tension in a pseudo-potential lattice Boltzmann model while keeping interface thickness and spurious currents constant, improving interface dynamics resolution. A method is developed to capture residual fluid components smaller than cell size using local constitutive relations, including absolute and relative permeability and capillary pressure curves. Additionally, a tensorial resistivity model is implemented for heterogeneous structures such as fiber bundles, aligning resistivity along principal axes determined from the Hessian and gradient of local porosity fields. Benchmark tests, including practical rock geometries, validate these enhancements, demonstrating improved transient interface dynamics, accurate capture of irreducible fluid components, and correct directional effects in under-resolved structures.

physics.flu-dyn↗

arXiv2025

A simulation approach including under-resolved scales for multi-component fluid flows in multi-scale porous structures

In this study, we develop computational models and methodology for accurate multi-component-flow simulation in under-resolved multi-scale porous structures. It is generally impractical to fully resolve the flow in porous structures with large length-scale difference due to tremendously high computational expense. The flow contributions from under-resolved scales need to be accounted for with proper physics modeling as well as simulation processes. Using pre-computed physical properties such as the absolute permeability, K0, the capillary-pressure-saturation curve, and the relative permeability, Kr, in typically resolved porous structures, local fluid force is conjectured and applied to simulation in the under-resolved regions that are represented by porous media. By doing so, accurate simulation of flow in multi-scale porous structures becomes feasible. In order to check the accuracy and robustness of this method, a set of benchmark test cases are performed for both single-component and multi-component flows in artificially constructed multi-scale porous structures, and simulation results are compared with analytic solutions and/or results with much finer resolution resolving the porous structures. Quantitatively consistent results are obtained with proper input of K0, capillary pressure, and Kr in all tested cases. Specifically, imbibition patterns, entry pressure, residual component patterns, and the absolute and relative permeability are accurately captured with this approach.

physics.flu-dyn↗

arXiv2024

Rapid, High-resolution and Distortion-free $R_{2}^{*}$ Mapping of Fetal Brain using Multi-echo Radial FLASH and Model-based Reconstruction

Purpose: To develop a rapid, high-resolution and distortion-free technique for simultaneous water-fat separation, $R_{2}^{*}$ and $B_{0}$ mapping of the fetal brain at 3T. Methods: A 2D multi-echo radial FLASH sequence with blip gradients is adapted for data acquisition during maternal free breathing. A calibrationless model-based reconstruction with sparsity constraints is developed to jointly estimate water, fat, $R_{2}^{*}$ and $B_{0}$ field maps directly from k-space. This approach was validated and compared to reference methods using numerical and NIST phantoms and data from nine fetuses between 26 and 36 weeks of gestation age. Results: Both numerical and experimental phantom studies confirm good accuracy and precision. In fetal studies, model-based reconstruction yields quantitative $R_{2}^{*}$ values in close agreement with those from a parallel imaging compressed sensing (PICS) technique using Graph Cut (intra-class correlation coefficient [ICC] = 0.9601), while providing enhanced image detail. Repeated scans confirm good reproducibility (ICC = 0.9213). Compared to multi-echo EPI, the proposed radial technique produces higher-resolution (1.1 $\times$ 1.1 $\times$ 3 mm$^{3}$ vs. 2-3 $\times$ 2-3 $\times$ 3 mm$^{3}$) $R_{2}^{*}$ maps with reduced distortion. Despite of differences in motion, resolution and distortion, $R_{2}^{*}$ values are comparable between the two acquisition strategies (ICC = 0.8049). Additionally, the proposed approach enables synthesis of high-resolution and distortion-free $R_{2}^{*}$-weighted images. Conclusion: This study demonstrates the feasibility of using multi-echo radial FLASH combined with calibrationless model-based reconstruction for motion-robust, distortion-free $R_{2}^{*}$ mapping of the fetal brain at 3T, achieving a nominal resolution of $1.1 \times 1.1 \times 3$ mm$^{3}$ within 2 seconds per slice.

physics.med-ph↗

arXiv2022

Deep-learning-enabled Brain Hemodynamic Mapping Using Resting-state fMRI

Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrive time (BAT) of the human brain using resting-state CO2 fluctuations as a natural 'contrast media'. The deep-learning network was trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which included data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibited excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging.

eess.IV↗

arXiv2016

Studies of accurate multi-component lattice Boltzmann models on benchmark cases required for engineering applications

We present recent developments in lattice Boltzmann modeling for multi-component flows, implemented on the platform of a general purpose, arbitrary geometry solver PowerFLOW. Presented benchmark cases demonstrate the method's accuracy and robustness necessary for handling real world engineering applications at practical resolution and computational cost. The key requirements for such approach are that the relevant physical properties and flow characteristics do not strongly depend on numerics. In particular, the strength of surface tension obtained using our new approach is independent of viscosity and resolution, while the spurious currents are significantly suppressed. Using a much improved surface wetting model, undesirable numerical artifacts including thin film and artificial droplet movement on inclined wall are significantly reduced.

physics.flu-dyn↗

arXiv2016

Simulation of residual oil displacement in a sinusoidal channel with the lattice Boltzmann method

We simulate oil slug displacement in a sinusoidal channel in order to validate computational models and algorithms for multi-component flow. This case fits in the gap between fully realistic cases characterized by complicated geometry and academic cases with simplistic geometry. Our computational model is based on the lattice Boltzmann method and allows for variation of physical parameters such as wettability and viscosity. The effect of variation of model parameters is analyzed, in particular via comparison with analytical solutions. We discuss the requirements for accurate solution of the oil slug displacement problem.

physics.flu-dyn↗