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Original Article

Simulation-Based FPGA Implementation of MRI Image Reconstruction Using 2D IFFT in Vivado

  • Paper ID 373
  • Volume 6, Issue 3
  • Pages 203-208
  • Published Online: May-June 2026
  • 15 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Kushi K S1
  • Yashvanth Gowda K S2
  • Jagadeesh Gowda B3
  • Saraswathi J M4
  • Poorvika T P5
  • Dr. Manoj Kumar S B6

1 2 3 B.E. Students, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, India. 4 5 Assistant Professor, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, India. 6 Associate Professor, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, India.

Article Information

Published Online
May-June 2026
Pages
203-208
Article Type
Original Article
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Abstract

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Magnetic resonance imaging (MRI) relies on transforming raw k-space measurements into clinically meaningful images, a process that is computationally intensive and time-sensitive. This work presents a simulation-based approach for MRI image reconstruction using a field-programmable gate array (FPGA) architecture developed in the Vivado design environment. The proposed method processes complex k-space data through a structured pipeline that includes memory-based data loading, two- dimensional inverse fast Fourier transform (2D-IFFT), magnitude computation, and intensity normalization to generate the final spatial- domain image. The design emphasizes a hardware-oriented workflow where data is handled in a sequential and parallel manner to improve processing efficiency compared to conventional software implementations. Initially validated in simulation, the system demonstrates correct reading and handling of memory-formatted k- space inputs and successful stage-wise transformation toward image reconstruction. The approach is designed with scalability in mind, allowing future integration with real FPGA hardware such as Artix-7 platforms and extension to multi-coil MRI systems. By focusing on efficient data flow and modular design, the proposed framework provides a practical foundation for developing real-time medical imaging solutions. This work contributes to the growing intersection of computational imaging and reconfigurable hardware, offering a pathway toward compact, high-performance MRI reconstruction systems suitable for next-generation biomedical applications.

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  • CrossRef DOI
  • ISSN 2583-0368
  • Open Access
  • Peer Reviewed
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