Detailed Information on Publication Record
2008
Simulation of fluorescence image formation in 3D light microscopy
KOZUBEK, Michal, David SVOBODA, Marek KAŠÍK, Martin MAŠKA, Jan HUBENÝ et. al.Basic information
Original name
Simulation of fluorescence image formation in 3D light microscopy
Name in Czech
Simulace formování fluorescenčního obrazu v 3D světelné mikroskopii
Authors
KOZUBEK, Michal, David SVOBODA, Marek KAŠÍK, Martin MAŠKA, Jan HUBENÝ, Stanislav STEJSKAL, Michal SEEMAN and Pavel ZEMČÍK
Edition
8th Meeting of European Light Microscopy Initiative, 2008
Other information
Language
English
Type of outcome
Konferenční abstrakt
Field of Study
20200 2.2 Electrical engineering, Electronic engineering, Information engineering
Country of publisher
Switzerland
Confidentiality degree
není předmětem státního či obchodního tajemství
Organization unit
Faculty of Informatics
Keywords in English
simulation; image formation; 3D light microscopy
Tags
International impact
Změněno: 12/6/2008 13:26, prof. RNDr. Michal Kozubek, Ph.D.
Abstract
V originále
Fluorescence microscopy still meets the problem of the quality of cell image analysis results. The majority of 2D as well as 3D cell image data acquired using fluorescence microscopy is typically of not very good quality (due to degradations caused by cell preparation, optics and electronics). That is why image processing algorithms applied to this data typically offer imprecise and unreliable results. As the ground truth (GT) for given image data is obviously not available the outputs of different image analysis methods can be neither verified nor compared to each other. In some papers, this problem is partially solved by estimating GT by experts in the field (biologists or physicians). However, in many cases such GT estimate is very subjective and strongly varies among different experts. In order to overcome these difficulties we have created a toolbox that can generate 3D models of artificial biological objects (cells and their components) along with their corresponding images degraded by specific optics and electronics. Image analysis methods can then be applied to such simulated image data. The analysis results (such as segmentation or measurement results) can be compared with GT derived from input models of objects (or measurements on them). In this way, image analysis methods can be compared to each other and their quality (based on difference from GT) can be computed. The present version of the simulation toolbox can generate cells in 3D using deformation of simple shapes and adding texture to the cell interior. Further, it can simulate optical degradations using convolution with supplied point spread function as well as electronic artifacts such as impulse hot pixel noise, additive readout-noise or Poisson photon-shot noise. We have also dealt with the task of evaluating the plausibility of the simulated images in terms of their similarity to real image data. We have tested several similarity criteria such as visual comparison, intensity histograms, central moments, frequency analysis and entropy. The simulation toolbox will be made freely available via simple web interface.
Links
| LC535, research and development project |
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| 2B06052, research and development project |
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