Paper
23 March 1995 Fluorescence photobleaching correction for expectation-maximization algorithm
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Proceedings Volume 2412, Three-Dimensional Microscopy: Image Acquisition and Processing II; (1995) https://doi.org/10.1117/12.205333
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States
Abstract
In 3D fluorescence microscopy, a series of 2D images is collected at different focal settings through the specimen. Each image in this series contains the in-focus plane plus contributions from out-of-focus structures that blur the image. Furthermore, as the series is collected the fluorescent dye in the specimen fades over time in response to the total excitation light dosage which progressively increase as more optical slices are collected. Thus the different optical slices are 2D images of different 3D objects, in the sense that at each time point, the object has a different overall intensity. To date, the approach to compensate for this decay has been to precondition the image by dividing the intensities in each optical slice by a decaying exponential before processing the image by any of a number of existing deblurring algorithms. We have now directly incorporated fluorescent decay into maximum-likelihood estimators for the 3D distribution of fluorescent dye. We derived a generalized expectation-maximization algorithm for the simultaneous estimation of the decay constant, considered homogeneous, and the distribution of fluorescent dye.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jose-Angel Conchello "Fluorescence photobleaching correction for expectation-maximization algorithm", Proc. SPIE 2412, Three-Dimensional Microscopy: Image Acquisition and Processing II, (23 March 1995); https://doi.org/10.1117/12.205333
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Cited by 17 scholarly publications.
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KEYWORDS
Expectation maximization algorithms

Luminescence

Algorithm development

Sensors

Microscopes

3D image processing

Detection and tracking algorithms

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