More IMPATIENT: A gridding-accelerated Toeplitz-based strategy for non-Cartesian high-resolution 3D MRI on GPUs

نویسندگان

  • Jiading Gai
  • Nady Obeid
  • Joseph L. Holtrop
  • Xiaolong Wu
  • Fan Lam
  • Maojing Fu
  • Justin P. Haldar
  • Wen-mei W. Hwu
  • Zhi-Pei Liang
  • Bradley P. Sutton
چکیده

Several recent methods have been proposed to obtain significant speed-ups in MRI image reconstruction by leveraging the computational power of GPUs. Previously, we implemented a GPU-based image reconstruction technique called the Illinois Massively Parallel Acquisition Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) for reconstructing data collected along arbitrary 3D trajectories. In this paper, we improve IMPATIENT by removing computational bottlenecks by using a gridding approach to accelerate the computation of various data structures needed by the previous routine. Further, we enhance the routine with capabilities for off-resonance correction and multi-sensor parallel imaging reconstruction. Through implementation of optimized gridding into our iterative reconstruction scheme, speed-ups of more than a factor of 200 are provided in the improved GPU implementation compared to the previous accelerated GPU code.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

More IMPATIENT: A Gridding-Accelerated Toeplitz-based Strategy for Non-Cartesian High-Resolution 3D MRI on GPU

Jiading Gai, Joseph Lee Holtrop, Xiao-Long Wu, Fan Lam, Maojing Fu, Justin P. Haldar, Wen-mei W. Hwu, Zhi-Pei Liang, and Bradley P. Sutton Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States, Department of Bioengineering, University of Illinois at UrbanaChampaign, Urbana, IL, United States, Electrical and Computer Engineering, University of Illinois at Urban...

متن کامل

Fast Regridding using LSQR on Graphics Hardware

Introduction: Iterative image reconstruction methods have become increasingly popular for parallel imaging or constrained reconstruction methods, but the main drawback is the long reconstruction time. In the case of nonCartesian imaging, resampling of k-space data between Cartesian and non-Cartesian grids has to be performed in each iteration step. Therefore the gridding procedure tends to be t...

متن کامل

Gridding & the NUFFT for Non-Cartesian Image Reconstruction

Introduction Typically MRI data is collected on in a rectilinear, or Cartesian, sampling pattern. Image reconstruction can then be performed with a simple 2D (or 3D) discrete Fourier transform. However, there is a long history of acquisition methods using non-Cartesian sampling patterns, going back to the very beginning of MRI. These include spiral and radial acquisition methods as shown in Fig...

متن کامل

On NUFFT-based gridding for non-Cartesian MRI.

For MRI with non-Cartesian sampling, the conventional approach to reconstructing images is to use the gridding method with a Kaiser-Bessel (KB) interpolation kernel. Recently, Sha et al. [L. Sha, H. Guo, A.W. Song, An improved gridding method for spiral MRI using nonuniform fast Fourier transform, J. Magn. Reson. 162(2) (2003) 250-258] proposed an alternative method based on a nonuniform FFT (N...

متن کامل

Accelerated reconstruction using parallel computing for spiral spectroscopic imaging

Introduction Over the years, the development of fast spectroscopic imaging techniques has found applications in full coverage CSI (chemical shift imaging) and/or high resolution CSI. Recently, the interest has continued with usage in areas such as real time metabolite imaging [1] and temperature mapping, which can be used in interventional procedures [2]. Of these fast spectroscopic imaging pro...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Journal of parallel and distributed computing

دوره 73 5  شماره 

صفحات  -

تاریخ انتشار 2013