Application of a laser speckle method for determining chemotactic response of Pseudomonas aeruginosas towards atractants

S. MURIALDO; L. PASSONI; G. H. SENDRA; H. RABAL; R. ARIZAGA; N. CAP; M. TRIVI

Nimes, Francia

Congreso; International Congress Speckle ’06; 2006

International Society for Optical Engineering (SPIE)

Dynamic speckle images are useful tools to characterize the activity of biological tissues. In this paper, this technique was applied to determine chemotaxis responses of Pseudomonas aeruginosa towards attractants. Generalized weighted differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application. Pseudomonas aeruginosa towards attractants. Generalized weighted differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application.