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
Link To Document :
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