{"title":"FPGA implementation of the coupled filtering method","authors":"C. Zhang, Tianzhu Liang, P. Mok, Weichuan Yu","doi":"10.1109/BIBM.2016.7822556","DOIUrl":null,"url":null,"abstract":"In ultrasound image analysis, speckle tracking methods are widely applied to study the elasticity of body tissue. However, “feature-motion decorrelation” still remains as a challenge for speckle tracking methods. Recently, a coupled filtering method was proposed to accurately estimate strain values when the tissue deformation is large. The major drawback of the new method is its high computational complexity. Even the GPU-based program requires a few hours to finish the analysis. In this paper, we propose an FPGA-based implementation for further acceleration. The capability of FPGAs on handling different image processing components in this method is discussed. The algorithm is reformulated to build a highly efficient pipeline on FPGA. The final implementation on a Xilinx Virtex-7 FPGA is 15 times faster than the GPU implementation on two NVIDIA graphic cards (GeForce GTX 580).","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In ultrasound image analysis, speckle tracking methods are widely applied to study the elasticity of body tissue. However, “feature-motion decorrelation” still remains as a challenge for speckle tracking methods. Recently, a coupled filtering method was proposed to accurately estimate strain values when the tissue deformation is large. The major drawback of the new method is its high computational complexity. Even the GPU-based program requires a few hours to finish the analysis. In this paper, we propose an FPGA-based implementation for further acceleration. The capability of FPGAs on handling different image processing components in this method is discussed. The algorithm is reformulated to build a highly efficient pipeline on FPGA. The final implementation on a Xilinx Virtex-7 FPGA is 15 times faster than the GPU implementation on two NVIDIA graphic cards (GeForce GTX 580).