COMPYDA: An online tool for verifying the similarity of image
datasets

D 2024

COMPYDA: An online tool for verifying the similarity of image datasets

NEČASOVÁ, Tereza; Daniel MÚČKA a David SVOBODA

Základní údaje

Originální název

COMPYDA: An online tool for verifying the similarity of image datasets

Autoři

NEČASOVÁ, Tereza; Daniel MÚČKA a David SVOBODA

Vydání

Athens, Greece, 2024 IEEE International Symposium on Biomedical Imaging (ISBI), od s. 1-5, 5 s. 2024

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

30200 3.2 Clinical medicine

Stát vydavatele

Řecko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/24:00135497

Organizační jednotka

Fakulta informatiky

ISBN

979-8-3503-1334-5

ISSN

Klíčová slova anglicky

Web-service;Statistics;Data validation;Image descriptors;Privacy;Augmented data

Štítky

cbia-web, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 7. 4. 2025 17:12, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Nowadays, when the vast majority of biomedical research relies on machine learning methods, paying attention to the meaningfulness of the data we work with is crucial. This is especially true if the dataset is scarce and we are required to use various augmentation techniques to enlarge training sets. The additional data are, however, not guaranteed to have the same characteristics as the original data, and therefore, the augmented set may be inconsistent. This can subsequently lead to incorrect training of biomedical image analysis methods, which may result in biased classification, detection, segmentation, or tracking results. In this paper, we present an online tool called COMPYDA, that allows users to easily assess the similarity of a pair of datasets using well-founded, commonly used statistic methods. COMPYDA guides users through univariate and multivariate analyses and helps them understand and explain dataset differences to ascertain a compatible dataset for further training. The tool is available at: https://cbia.fi.muni.cz/compyda/

Návaznosti

EF18_046/0016045, projekt VaV

Název: Modernizace národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging

MUNI/A/1592/2023, interní kód MU

Název: Modelování, analýza a verifikace (2024)

Investor: Masarykova univerzita, Modelování, analýza a verifikace (2024)

90250, velká výzkumná infrastruktura

Název: Czech-BioImaging III

Citovat

NEČASOVÁ, Tereza; Daniel MÚČKA a David SVOBODA. COMPYDA: An online tool for verifying the similarity of image datasets. Online. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). Athens, Greece: IEEE, 2024, s. 1-5. ISBN 979-8-3503-1334-5. Dostupné z: https://doi.org/10.1109/ISBI56570.2024.10635415.

@inproceedings{2372158,
   author = {Nečasová, Tereza and Múčka, Daniel and Svoboda, David},
   address = {Athens, Greece},
   booktitle = {2024 IEEE International Symposium on Biomedical Imaging (ISBI)},
   doi = {https://doi.org/10.1109/ISBI56570.2024.10635415},
   keywords = {Web-service;Statistics;Data validation;Image descriptors;Privacy;Augmented data},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Athens, Greece},
   isbn = {979-8-3503-1334-5},
   pages = {1-5},
   publisher = {IEEE},
   title = {COMPYDA: An online tool for verifying the similarity of image datasets},
   url = {https://ieeexplore.ieee.org/document/10635415},
   year = {2024}
}

TY  - CONF
ID  - 2372158
AU  - Nečasová, Tereza - Múčka, Daniel - Svoboda, David
PY  - 2024
TI  - COMPYDA: An online tool for verifying the similarity of image datasets
PB  - IEEE
CY  - Athens, Greece
SN  - 9798350313345
KW  - Web-service;Statistics;Data validation;Image descriptors;Privacy;Augmented data
UR  - https://ieeexplore.ieee.org/document/10635415
N2  - Nowadays, when the vast majority of biomedical research relies on machine learning methods, paying attention to the meaningfulness of the data we work with is crucial. This is especially true if the dataset is scarce and we are required to use various augmentation techniques to enlarge training sets. The additional data are, however, not guaranteed to have the same characteristics as the original data, and therefore, the augmented set may be inconsistent. This can subsequently lead to incorrect training of biomedical image analysis methods, which may result in biased classification, detection, segmentation, or tracking results. In this paper, we present an online tool called COMPYDA, that allows users to easily assess the similarity of a pair of datasets using well-founded, commonly used statistic methods. COMPYDA guides users through univariate and multivariate analyses and helps them understand and explain dataset differences to ascertain a compatible dataset for further training. The tool is available at: https://cbia.fi.muni.cz/compyda/
ER  -

NEČASOVÁ, Tereza; Daniel MÚČKA a David SVOBODA. COMPYDA: An online tool for verifying the similarity of image datasets. Online. In \textit{2024 IEEE International Symposium on Biomedical Imaging (ISBI)}. Athens, Greece: IEEE, 2024, s.~1-5. ISBN~979-8-3503-1334-5. Dostupné z: https://doi.org/10.1109/ISBI56570.2024.10635415.

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