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 a David SVOBODA

Základní údaje

Originální název

Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data

Autoři

NEČASOVÁ, Tereza (203 Česká republika, domácí) a David SVOBODA (203 Česká republika, domácí)

Vydání

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

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Impakt faktor

Impact factor: 0.402 v roce 2005

Kód RIV

RIV/00216224:14330/19:00107168

Organizační jednotka

Fakulta informatiky

ISBN

978-3-030-11023-9

ISSN

DOI

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

UT WoS

000594200000028

Klíčová slova anglicky

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

Štítky

cbia-web

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 4. 2020 22:24, RNDr. Pavel Šmerk, Ph.D.

Anotace

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.

Návaznosti

GA17-05048S, projekt VaV

Název: Segmentace a trekování živých buněk v multimodálních obrazech

Investor: Grantová agentura ČR, Segmentace a trekování živých buněk v multimodálních obrazech

MUNI/A/0854/2017, interní kód MU

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

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII., DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

Citovat

NEČASOVÁ, Tereza a 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, s. 385-394. ISBN 978-3-030-11023-9. Dostupné z: 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  - CONF
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 a 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, s.~385-394. ISBN~978-3-030-11023-9. Dostupné z: https://dx.doi.org/10.1007/978-3-030-11024-6\_{}28.

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