Visual and Quantitative Comparison of Real and Simulated
Biomedical Image Data

D 2019

Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data

NEČASOVÁ, Tereza and David SVOBODA

Basic information

Original name

Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data

Authors

NEČASOVÁ, Tereza (203 Czech Republic, belonging to the institution) and David SVOBODA (203 Czech Republic, belonging to the institution)

Edition

LNCS 11134. Munich, Germany, Computer Vision – ECCV 2018 Workshops, p. 385-394, 10 pp. 2019

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/19:00107168

Organization unit

Faculty of Informatics

ISBN

978-3-030-11023-9

ISSN

DOI

http://dx.doi.org/10.1007/978-3-030-11024-6_28

UT WoS

000594200000028

Keywords in English

Feature comparison; Validation of simulation; Statistical evaluation; Similarity visualisation

Abstract

V originále

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.

Links

GA17-05048S, research and development project

Name: Segmentace a trekování živých buněk v multimodálních obrazech

Investor: Czech Science Foundation

MUNI/A/0854/2017, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII.

Investor: Masaryk University, Category A

Citovat

NEČASOVÁ, Tereza and David SVOBODA. Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data. In Laura Leal-Taixé, Stefan Roth. 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.

@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.

Detailed Information on Publication Record