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

作     者：Hadj Fredj, Amira Malek, Jihene 

作者机构：Monastir Univ Fac Sci Monastir Lab Elect & Microelect Monastir Tunisia Sousse Univ Higher Inst Appl Sci & Technol Sousse Sousse Tunisia 

出 版 物：《JOURNAL OF REAL-TIME IMAGE PROCESSING》 (实时图像处理杂志)

年 卷 期：2021年第18卷第6期

页      面：2429-2440页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Denoising algorithms Anisotropic diffusion filter Segmentation Medical application SW HW codesign ZYNQ-7 ZC702 

摘      要：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.