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 and David SVOBODA

Basic information

Original name

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

Authors

NEČASOVÁ, Tereza (203 Czech Republic, guarantor, belonging to the institution), Daniel MÚČKA (703 Slovakia, belonging to the institution) and David SVOBODA (203 Czech Republic, belonging to the institution)

Edition

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

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

30200 3.2 Clinical medicine

Country of publisher

Greece

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

Organization unit

Faculty of Informatics

ISBN

979-8-3503-1334-5

ISSN

DOI

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

Keywords in English

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

Abstract

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/

Links

LM2023050, research and development project

Name: Národní infrastruktura pro biologické a medicínské zobrazování

Investor: Ministry of Education, Youth and Sports of the CR, Czech BioImaging: National research infrastructure for biological and medical imaging

MUNI/A/1592/2023, interní kód MU

Name: Modelování, analýza a verifikace (2024)

Investor: Masaryk University, Modeling, analysis, and verification (2024)

Citovat

NEČASOVÁ, Tereza, Daniel MÚČKA and 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, p. 1-5. ISBN 979-8-3503-1334-5. Available from: 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 and 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, p.~1-5. ISBN~979-8-3503-1334-5. Available from: https://dx.doi.org/10.1109/ISBI56570.2024.10635415.

Detailed Information on Publication Record