DocumentCode
2060414
Title
Benchmarking image-processing algorithms for biomicroscopy: Reference datasets and perspectives
Author
Sage, Daniel ; Kirshner, Hagai ; Vonesch, Cedric ; Lefkimmiatis, Stamatios ; Unser, Michael
Author_Institution
Biomed. Imaging Group, Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
fYear
2013
fDate
9-13 Sept. 2013
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
bioinformatics; biomedical optical imaging; fluorescence; image reconstruction; medical image processing; optical microscopy; 3D continuous domain model; benchmarking image processing algorithm; bioimage informatics; bioimaging dataset simulation; biological structure; biomicroscopy; fluorescence microscopy quantitative tool; image formation; image reconstruction algorithm; performance criteria; physically realistic model; Biological system modeling; Computational modeling; Deconvolution; Fluorescence; Microscopy; Bioimage informatics; benchmarking; fluorescence microscopy; simulated datastets;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location
Marrakech
Type
conf
Filename
6811705
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