Robust incremental compensation of the light attenuation with depth in 3D fluorescence microscopy

Summary Fluorescent signal intensities from confocal laser scanning microscopes (CLSM) suffer from several distortions inherent to the method. Namely, layers which lie deeper within the specimen are relatively dark due to absorption and scattering of both excitation and fluorescent light, photobleac...

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Bibliographic Details
Published in:Journal of microscopy (Oxford) 2004-06, Vol.214 (3), p.297-314
Main Authors: KERVRANN, C., LEGLAND, D., PARDINI, L.
Format: Article
Language:English
Subjects:
3D microscopy
Algorithms
Animals
Colon - cytology
Colon - ultrastructure
computer vision
confocal microscopy
depth correction
DNA - analysis
fluorescence
Image Enhancement - methods
Image Processing, Computer-Assisted - methods
image restoration
Imaging, Three-Dimensional - methods
intensity loss
Key words
Light
Lycopersicon esculentum - ultrastructure
Microscopy, Confocal - methods
Microscopy, Fluorescence - methods
photobleaching
Rats
regularization
robust estimation
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Summary:Summary Fluorescent signal intensities from confocal laser scanning microscopes (CLSM) suffer from several distortions inherent to the method. Namely, layers which lie deeper within the specimen are relatively dark due to absorption and scattering of both excitation and fluorescent light, photobleaching and/or other factors. Because of these effects, a quantitative analysis of images is not always possible without correction. Under certain assumptions, the decay of intensities can be estimated and used for a partial depth intensity correction. In this paper we propose an original robust incremental method for compensating the attenuation of intensity signals. Most previous correction methods are more or less empirical and based on fitting a decreasing parametric function to the section mean intensity curve computed by summing all pixel values in each section. The fitted curve is then used for the calculation of correction factors for each section and a new compensated sections series is computed. However, these methods do not perfectly correct the images. Hence, the algorithm we propose for the automatic correction of intensities relies on robust estimation, which automatically ignores pixels where measurements deviate from the decay model. It is based on techniques adopted from the computer vision literature for image motion estimation. The resulting algorithm is used to correct volumes acquired in CLSM. An implementation of such a restoration filter is discussed and examples of successful restorations are given.
ISSN:0022-2720
1365-2818
DOI:10.1111/j.0022-2720.2004.01333.x