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@misc{1201853,
author = {Svoboda, David and Kozubek, Michal},
booktitle = {Hands-on Image Processing, Robotiker-Tecnalia, Bilbao, Spain},
keywords = {simulation; biomedical imaging; fluorescence microscopy; cell nucleus},
language = {eng},
title = {CytoPacq – On-line Framework for Simulating Fluorescence Microscopy Images},
year = {2009}
}
TY - SLIDE
ID - 1201853
AU - Svoboda, David - Kozubek, Michal
PY - 2009
TI - CytoPacq – On-line Framework for Simulating Fluorescence Microscopy Images
KW - simulation
KW - biomedical imaging
KW - fluorescence microscopy
KW - cell nucleus
N2 - In recent years, the biomedicine, like the other fields of research, has become more and more tied up with the computer science. The vast majority of measurements is acquired, stored and further evaluated using the instruments controlled by the appropriate computer hardware and software. In optical microscopy such an equipment has already become a standard. The whole process of observation can be typically split into four principal parts: 1. Specimen preparation, 2. Image transmission, 3. Image acquisition, 4. Image analysis. In the last step of this process a large variety of image processing methods is used. It is clear that the quality and correctness of results of such methods influence the final evaluation and conclusions. That is why each user has to verify whether the selected method is appropriate and whether it performs correctly. For this purpose, we implemented a simulation toolbox called CytoPacq (http://cbia.fi.muni.cz/simulator/) that is capable of simulating the first three steps: * 3D-CytoGen ... generates the digital phantom (specimen preparation) * 3D-OptiGen ... imitates the whole optical system (image transmission) * 3D-AcquiGen ... simulates the behavior of CCD camera (image acquisition) As a result, CytoPacq generates selected synthetic image data as they would look like if acquired by real microscope and camera. Furthermore, the ideal image of an unaffected specimen is also generated. Hence, the synthetic data can be submitted to any image analysis method and the results of such method can be simply compared to the ideal image and the quality can be evaluated. Currently, three types of objects can be generated (microspheres, nuclei of HL-60 cells, and nuclei of granulocytes). The generation of new types of phantoms (e.g. tissue clusters) is currently under development.
ER -
SVOBODA, David a Michal KOZUBEK. CytoPacq – On-line Framework for Simulating Fluorescence Microscopy Images. In \textit{Hands-on Image Processing, Robotiker-Tecnalia, Bilbao, Spain}. 2009.
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