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@inproceedings{1427778,
author = {Nečasová, Tereza and Svoboda, David},
address = {Munich, Germany},
booktitle = {Computer Vision – ECCV 2018 Workshops},
doi = {http://dx.doi.org/10.1007/978-3-030-11024-6_28},
edition = {LNCS 11134},
editor = {Laura Leal-Taixé, Stefan Roth},
keywords = {Feature comparison; Validation of simulation; Statistical evaluation; Similarity visualisation},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Munich, Germany},
isbn = {978-3-030-11023-9},
pages = {385-394},
publisher = {Springer},
title = {Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data},
url = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-11024-6_28.pdf},
year = {2019}
}
TY - JOUR
ID - 1427778
AU - Nečasová, Tereza - Svoboda, David
PY - 2019
TI - Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data
PB - Springer
CY - Munich, Germany
SN - 9783030110239
KW - Feature comparison
KW - Validation of simulation
KW - Statistical evaluation
KW - Similarity visualisation
UR - https://link.springer.com/content/pdf/10.1007%2F978-3-030-11024-6_28.pdf
L2 - https://link.springer.com/content/pdf/10.1007%2F978-3-030-11024-6_28.pdf
N2 - The simulations in biomedical image analysis provide a solution when the real image data are difficult to be annotated or if they are available only in small quantities. The progress in simulations rapidly grows in the recent years. Nevertheless, the comparative techniques for the assessment of the plausibility of generated data are still unsatisfactory or none. This paper aims to point out the problem of insufficient comparison of real and synthetic data, which is done in many cases only by visual inspection or based on subjective measurements. The selected texture features are first compared in a univariate manner by quantile-quantile plots and Kolmogorov-Smirnov test. The evaluation is then extended into multivariate assessment using the PCA for a visualization and furthermore for a quantitative measure of similarity by Jaccard index. Two different image datasets were used to show the results and the importance of the validation of simulated data in many aspects.
ER -
NEČASOVÁ, Tereza and David SVOBODA. Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data. In Laura Leal-Taixé, Stefan Roth. \textit{Computer Vision – ECCV 2018 Workshops}. LNCS 11134. Munich, Germany: Springer, 2019, p.~385-394. ISBN~978-3-030-11023-9. Available from: https://dx.doi.org/10.1007/978-3-030-11024-6\_{}28.
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