Monitoring of rhythms in laset speckle data  

作　　者：D.E.Postnov A.Y.Neganova D.D.Postnov A.R.Brazhe 

机构地区：[1]Physics Department,Saratov State University Astrakhanskaya St.83,Saratov 410012,Russia [2]Biophysics Department,Biological Facuty,Moscow State UniversityLeninskie Gory 1,Building 12,119991 Moscow,Russia

出　　处：《Journal of Innovative Optical Health Sciences》2014年第3期73-82,共10页创新光学健康科学杂志（英文）

摘　　要：While the laser speckle imaging(LSI)is a powerful tool for multiple biomedical applications,suchas monitoring of the blood flow,in many cases it can provide additional information when combined with spatio-temporal rhythm analysis.We demonstrate the application of GraphicsProcessing Units(GPU)-based rhythm analysis for the post procesing of LSI data,discuss therelevant structure of GPU-based computations,test the proposed technique on surrogate 3D data,and apply this approach to kidney blood fiow autoregulation.Experiments with surrogate data demonstrate the ability of the method to extract information about oscillation patterns fromnoisy data,as well as to detect the moving source of the rhythm.The analysis of kidney dataallow us to detect and to localize the dymamics arising from autoregulation processes at the levelof individual nephrons(tubuloglomerular feedback(TGF)rhythm),as well as to distinguishbetween the TGF-active and the TGF-silent zones.

关 键 词：Laser speckle imaging wavelet transform kidney autoregulation. 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]