FPGA-accelerated anisotropic diffusion filter based on SW/HW-codesign for medical images


In medical imaging, denoising is very important for the analysis of images and the diagnosis and treatment of diseases. Currently, the image denoising methods based on anisotropic diffusion are efficient. However, the methods have been limited as regards the processing time. In recent computing systems, the FPGA-based acceleration has been highly competitive for GPU-based one due to its high computation capabilities and lower energy consumption. In this paper, we present a high-level synthesis implementation on a SOC-FPGA of an anisotropic diffusion algorithm dedicated to medical applications. We choose an oriented speckle reducing anisotropic diffusion denoising filter, which provides robust performance but requires a significant computation on the embedded CPU since it is iterative. Moreover, we optimize the performance by modifying the original algorithm, automizing it by controlling the diffusion process at each iteration, and accelerating the processing operations by providing a hardware/software description. The evaluation is performed using different medical images. The efficiency and relevance of the proposed filter is demonstrated through segmentation. The design is validated on FPGA XC7Z020CLG484-1 with a frequency of 255 MHz and a PSNR of about 30 dB.

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Correspondence to Amira Hadj Fredj.

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Hadj Fredj, A., Malek, J. FPGA-accelerated anisotropic diffusion filter based on SW/HW-codesign for medical images. J Real-Time Image Proc (2021). https://doi.org/10.1007/s11554-021-01100-3

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  • Denoising algorithms
  • Anisotropic diffusion filter
  • Segmentation
  • Medical application
  • SW/HW codesign
  • ZYNQ-7 ZC702