SPECTROSCOPY, IMAGING, OTHER TECHNIQUES |
Automated Detection of Elementary Calcium Release Events
Using the À Trous Wavelet Transform
Frederic von Wegner 1, Martin Both 1 and Rainer H A Fink 1*
1 University of Heidelberg
* To whom correspondence should be addressed. E-mail: rainer.fink{at}urz.uni-heidelberg.de.
Submitted on July 29, 2005
Revised on September 26, 2005
Accepted on 18 November 2005
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Abstract |
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We developed an algorithm for the automated detection and analysis of elementary Ca2+ release events (ECRE) based on the two-dimensional non-decimated wavelet transform. The transform is computed with the 'à trous' algorithm using the cubic B-spline as the basis function and yields a multiresolution analysis (MRA) of the image. This transform allows for highly efficient noise reduction while preserving signal amplitudes. ECRE detection is performed at the wavelet levels, thus using the whole spectral information contained in the image. The algorithm was tested on synthetic data at different noise levels as well as on experimental data of ECRE. The noise dependence of the statistical properties of the algorithm (detection sensitivity and reliability) was determined from synthetic data and detection parameters were selected in order to optimize the detection of experimental ECRE. The wavelet based method shows considerably higher detection sensitivity and less false-positive counts than previously employed methods. It allows a more efficient detection of elementary Ca2+ release events than conventional methods, in particular in the presence of elevated background noise levels. The subsequent analysis of the morphological parameters of ECRE is reliably reproduced by the analysis procedure which is applied to the median filtered raw data. Testing the algorithm more rigorously showed that event parameter histograms (amplitude, rise time, FDHM, FWHM) were faithfully extracted from synthetic, 'in-focus' and 'out-of-focus' line scan sparks. Most importantly, ECRE obtained with laser scanning confocal microscopy of chemically skinned mammalian skeletal muscle fibres could be analysed automatically to reproducibly establish event parameter histograms. In summary, our method provides a new valuable tool for highly reliable automated detection of ECRE in muscle but can also be adapted to other preparations.
Key Words:
Calcium Sparks, Wavelet Transform
