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Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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Accelerating GRAPPA reconstruction using SoC design for real-time cardiac MRI.

Abdul Basit1, Omair Inam1, Hammad Omer1

  • 1Medical Image Processing Research Group (MIPRG), Department of Electrical and Computer Engineering, COMSATS University Islamabad, Pakistan.

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Summary

This study introduces a novel FPGA-based GRAPPA accelerator for faster cardiac MRI reconstruction. The hardware significantly speeds up image processing, enabling real-time cardiovascular imaging with high accuracy.

Keywords:
Cardiac MRIFPGAGRAPPAHardware acceleratorsMagnetic resonance imaging (MRI)

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Area of Science:

  • Medical Imaging
  • Hardware Acceleration
  • Cardiovascular Diseases

Background:

  • Real-time cardiac MRI (CMR) is crucial for diagnosing cardiovascular diseases but faces challenges with high frame rates and temporal resolution.
  • Existing methods like compressed sensing and parallel MRI (e.g., GRAPPA) improve CMR quality but demand substantial computational power, limiting real-time applications.
  • Field-programmable gate arrays (FPGAs) offer a potential hardware solution to accelerate computationally intensive MRI reconstruction algorithms.

Purpose of the Study:

  • To develop and evaluate a novel 32-bit floating-point FPGA-based GRAPPA accelerator.
  • To enhance the speed and efficiency of cardiac MR image reconstruction for real-time clinical applications.
  • To explore the trade-offs between reconstruction time, resource utilization, and design effort using FPGAs.

Main Methods:

  • Designed a custom FPGA architecture featuring dedicated computational engines (DCEs) for continuous data flow between GRAPPA calibration and synthesis stages.
  • Integrated a high-speed DDR4-SDRAM module for multi-coil MR data storage and an on-chip ARM Cortex-A53 processor for data transfer management.
  • Implemented the accelerator on a Xilinx Zynq UltraScale+ MPSoC using high-level synthesis (HLS) and hardware descriptive language (HDL).
  • Evaluated performance using in-vivo cardiac datasets (18- and 30-receiver coils) and compared with CPU and GPU-based GRAPPA methods.

Main Results:

  • The FPGA-based GRAPPA accelerator achieved speed-up factors of up to 121x compared to CPU-based methods and 9x compared to GPU-based methods.
  • Demonstrated reconstruction rates of up to approximately 27 frames-per-second.
  • Maintained the visual quality of reconstructed cardiac MR images.

Conclusions:

  • The proposed FPGA-based GRAPPA accelerator significantly accelerates cardiac MR image reconstruction.
  • This hardware solution enables higher frame rates and real-time imaging capabilities for clinical applications.
  • FPGA acceleration offers a promising approach to overcome computational bottlenecks in advanced MRI techniques.