All Publications


  • Motion-robust reconstruction of multishot diffusion-weighted images without phase estimation through locally low-rank regularization MAGNETIC RESONANCE IN MEDICINE Hu, Y., Levine, E. G., Tian, Q., Moran, C. J., Wang, X., Taviani, V., Vasanawala, S. S., Mcnab, J. A., Daniel, B. L., Hargreaves, B. A. 2019; 81 (2): 1181–90

    View details for DOI 10.1002/mrm.27488

    View details for Web of Science ID 000462086300038

  • Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR). Magnetic resonance in medicine Hu, Y., Wang, X., Tian, Q., Yang, G., Daniel, B., McNab, J., Hargreaves, B. 2019

    Abstract

    To resolve the motion-induced phase variations in multi-shot multi-direction diffusion-weighted imaging (DWI) by applying regularization to magnitude images.A nonlinear model was developed to estimate phase and magnitude images separately. A locally low-rank regularization (LLR) term was applied to the magnitude images from all diffusion-encoding directions to exploit the spatial and angular correlation. In vivo experiments with different resolutions and b-values were performed to validate the proposed method.The proposed method significantly reduces the noise level compared to the conventional reconstruction method and achieves submillimeter (0.8mm and 0.9mm isotropic resolutions) DWI with a b-value of 1,000  s / mm 2 and 1-mm isotropic DWI with a b-value of 2,000  s / mm 2 without modification of the sequence.A joint reconstruction method with spatial-angular LLR regularization on magnitude images substantially improves multi-direction DWI reconstruction, simultaneously removes motion-induced phase artifacts, and denoises images.

    View details for DOI 10.1002/mrm.28025

    View details for PubMedID 31593337

  • Motion-robust reconstruction of multishot diffusion-weighted images without phase estimation through locally low-rank regularization. Magnetic resonance in medicine Hu, Y., Levine, E. G., Tian, Q., Moran, C. J., Wang, X., Taviani, V., Vasanawala, S. S., McNab, J. A., Daniel, B. A., Hargreaves, B. L. 2018

    Abstract

    PURPOSE: The goal of this work is to propose a motion robust reconstruction method for diffusion-weighted MRI that resolves shot-to-shot phase mismatches without using phase estimation.METHODS: Assuming that shot-to-shot phase variations are slowly varying, spatial-shot matrices can be formed using a local group of pixels to form columns, in which each column is from a different shot (excitation). A convex model with a locally low-rank constraint on the spatial-shot matrices is proposed. In vivo brain and breast experiments were performed to evaluate the performance of the proposed method.RESULTS: The proposed method shows significant benefits when the motion is severe, such as for breast imaging. Furthermore, the resulting images can be used for reliable phase estimation in the context of phase-estimation-based methods to achieve even higher image quality.CONCLUSION: We introduced the shot-locally low-rank method, a reconstruction technique for multishot diffusion-weighted MRI without explicit phase estimation. In addition, its motion robustness can be beneficial to neuroimaging and body imaging.

    View details for PubMedID 30346058