Contact

  • Academic
    nurdaiza@stanford.edu
    University - Student Department: Rad/Radiological Sciences Laboratory Position: Graduate
    University - Student Department: Computer Science Position: Graduate

Additional Info

  • Mail Code: 5488

All Publications

  • T 2 $$ {\boldsymbol{T}}_{\mathbf{2}} $$ -Weighted Imaging of Water, Fat and Silicone. Magnetic resonance in medicine Nurdinova, A., Zhou, X., Oscanoa, J. A., Shah, P., Setsompop, K., Daniel, B. L., Hargreaves, B. A. 2026

    Abstract

    Magnetic resonance imaging (MRI) is a sensitive method for assessing silicone implant integrity, with T 2 $$ {\boldsymbol{T}}_{\mathbf{2}} $$ -weighted imaging being essential for detecting abnormalities in surrounding tissue. Silicone breast imaging protocols often require multiple tailored sequences for species suppression and diagnostic contrast. We propose a single sequence suitable for patients with or without implants that enables T 2 $$ {\boldsymbol{T}}_{\mathbf{2}} $$ -weighted, high-quality imaging and three-species separation within a clinically feasible scan time.Our approach uses a 2D fast spin echo (FSE) sequence with seven bipolar multi-echo gradient echo readouts, enabling field mapping and water-fat-silicone separation. Incoherent k y $$ {k}_y $$ - T E $$ TE $$ undersampling combined with joint multi-echo reconstruction leverages temporal correlations and applies compressed sensing regularization directly to the separated species.We achieve high-resolution, artifact-free water, fat, and silicone (WFS) images across three planes from one sequence, regardless of shim quality, and for different breast implant types. Compared to independent echo reconstruction and separation, joint multi-echo reconstruction with incoherent k y $$ {k}_y $$ - T E $$ TE $$ sampling allows acceleration of R = 6 $$ R=6 $$ , reducing scan time to 2.5 minutes.We demonstrate a robust T 2 $$ {\boldsymbol{T}}_{\mathbf{2}} $$ -weighted technique that provides reliable water-fat-silicone imaging in 2.5 minutes, enabling uniform breast protocols for patients with and without silicone implants.

    View details for DOI 10.1002/mrm.70253

    View details for PubMedID 41569099

  • Neural Space-Time Modeling for Motion-Corrected MR Reconstruction Nurdinova, A., Huang, W., Abraham, D., Bae, J., Lin, Y., Setsompop, K., Hargreaves, B. edited by Felsner, L., Kustner, T., Maier, A., Qin, C., Ahmadi, S. A., Kazi, A., Hu SPRINGER INTERNATIONAL PUBLISHING AG. 2026: 118-128

    View details for DOI 10.1007/978-3-032-06103-4_12

    View details for Web of Science ID 001685837600012

  • Gpu-accelerated JEMRIS for extensive MRI simulations. Magma (New York, N.Y.) Nurdinova, A., Ruschke, S., Gestrich, M., Stelter, J., Karampinos, D. C. 2025

    Abstract

    To enable accelerated Bloch simulations by enhancing the open-source multi-purpose MRI simulation tool JEMRIS with graphic processing units (GPU) parallelization.A GPU-compatible version of JEMRIS was built by shifting the computationally expensive parallelizable processes to the GPU to benefit from heterogeneous computing and by adding asynchronous communication and mixed precision support. With key classes reimplemented in CUDA C++, the developed GPU-JEMRIS framework was tested on simulations of common MRI artifacts in numerical phantoms. The accuracy and performance of the GPU-parallelized JEMRIS simulator were benchmarked against the CPU-parallelized JEMRIS and GPU-enabled KomaMRI.jl simulators. Additionally, an example of liver fat quantification errors due to respiratory motion artifacts was simulated in a multi-echo gradient echo (MEGRE) acquisition.The GPU-accelerated JEMRIS achieved speed-up factors 3-12 and 7-65 using double and single precision numerical integrators, respectively, when compared to the parallelized CPU implementation in the investigated numerical phantom scenarios. While double precision GPU simulations negligibly differ (<0.1% NRMSE) from double precision CPU simulations, the single precision simulations still present small errors of up to 1% k-space signal NRMSE. The developed a GPU extension enabled computationally demanding motion simulations with a multi-species abdominal phantom and a MEGRE sequence, showing significant and spatially varying fat fraction bias in the presence of motion.By solving the Bloch equations in parallel on device, accelerated Bloch simulations can be performed on any GPU-equipped device with CUDA support using the developed GPU-JEMRIS. This would enable further insights into more realistic large spin pool MR simulations such as experiments with large multi-dimensional phantoms, multiple chemical species and dynamic effects.

    View details for DOI 10.1007/s10334-025-01281-z

    View details for PubMedID 40906323

    View details for PubMedCentralID 8057531