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Benchmarking Image-Processing Algorithms for Biomicroscopy: Reference Datasets and Perspectives

D. Sage, H. Kirshner, C. Vonesch, S. Lefkimmiatis, M. Unser

Proceedings of the Twenty-First European Signal Processing Conference (EUSIPCO'13), Marrakech, Kingdom of Morocco, September 9-13, 2013, paper no. 1569744665.



As the field of bioimage informatics matures, the issue of the validation of image reconstruction algorithms and the definition of proper performance criteria becomes more pressing. In this work, we discuss benchmarking aspects of fluorescence microscopy quantitative tools. We point out the importance of generating realistic datasets and describe our approach to this task. We rely on our experience and present arguments in favor of the use of 3D continuous-domain models of biological structures for simulating bioimaging datasets. We also present physically-realistic models of image formation that that are reasonably efficiently to implement.


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