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 (203 Česká republika, garant, domácí), Daniel MÚČKA (703 Slovensko, domácí) a David SVOBODA (203 Česká republika, domácí)

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

Organizační jednotka

Fakulta informatiky

ISBN

979-8-3503-1334-5

ISSN

DOI

http://dx.doi.org/10.1109/ISBI56570.2024.10635415

Klíčová slova anglicky

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

Štítky

cbia-web

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 31. 10. 2024 13:12, doc. RNDr. David Svoboda, 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

LM2023050, projekt VaV

Název: Národní infrastruktura pro biologické a medicínské zobrazování

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Czech BioImaging: Národní výzkumná infrastruktura pro biologické a medicínské zobrazování

MUNI/A/1592/2023, interní kód MU

Název: Modelování, analýza a verifikace (2024)

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

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://dx.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 = {http://dx.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  - JOUR
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://dx.doi.org/10.1109/ISBI56570.2024.10635415.

Podrobný výpis o publikaci