Abstract

BiaPy is an open-source library and application that streamlines the use of common deep learning approaches for bioimage analysis. Designed to simplify technical complexities, it offers an intuitive interface, zero-code notebooks, and Docker integration, catering to both users and developers. While focused on deep learning workflows for 2D and 3D image data, it enhances performance with multi-GPU capabilities, memory optimization, and scalability for large datasets. Although BiaPy does not encompass all aspects of bioimage analysis, such as visualization and manual annotation tools, it empowers researchers by providing a ready-to-use environment with customizable templates that facilitate sophisticated bioimage analysis workflows.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* We have refined our framing of user-friendly bioimage analysis tools in the manuscript, ensuring fairness and accuracy in describing their features and accessibility.

* https://biapyx.github.io

Details

Title
BiaPy: Accessible deep learning on bioimages
Author
Franco-Barranco, Daniel; Andres-San Roman, Jesus Angel; Hidalgo-Cenalmor, Ivan; Backova, Lenka; Gonzalez-Marfil, Aitor; Clement Caporal; Chessel, Anatole; Gomez-Galvez, Pedro; Escudero, Luis M; Donglai Wei; Munoz-Barrutia, Arrate; Arganda-Carreras, Ignacio
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2025
Publication date
Jan 24, 2025
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2922244165
Copyright
© 2025. This article is published under http://creativecommons.org/licenses/by/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.