• DocumentCode
    3571345
  • Title

    GPU-based Method for Denoising Time Series of Fluorescent Imaging Data

  • Author

    Pelic, Denis ; Lukac, Niko ; Alik, Borut

  • Author_Institution
    Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
  • fYear
    2014
  • Firstpage
    360
  • Lastpage
    366
  • Abstract
    This paper presents a GPU-based method for denoising of time series images obtained by confocal microscopy, in order to study the oscillations of calcium and membrane voltage potential in beta cells. Since denoising of captured images is one of the first crucial steps, it is desirable that it is highly efficient and fast. This is especially important when dealing with a large number of time series images, where the computational complexity increases tremendously. Results demonstrate that the proposed method is at least 5 times faster, in comparison with a CPU-based implementation, while retaining the same accuracy.
  • Keywords
    computational complexity; graphics processing units; image denoising; time series; CPU based implementation; GPU based method; calcium voltage; computational complexity; confocal microscopy; denoising time series; fluorescent imaging data; membrane voltage; time series images; Graphics processing units; Imaging; Kernel; Noise; Noise reduction; Oscillators; Time series analysis; CUDA; GPGPU; denoising; fluorescent calcium imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing and Networking (CANDAR), 2014 Second International Symposium on
  • Type

    conf

  • DOI
    10.1109/CANDAR.2014.77
  • Filename
    7052210