Rethinking deep learning in bioimaging through a data centric lens

Jiajun Cao; Jan Wenzel; Shanghang Zhang; Josephine Lampe; Hongxiao Wang; Jiachen Yao; Zhicheng Zhang; Shuo Zhao; Yu Zhou; Chao Chen; Markus Schwaninger; Jufeng Yang; Danny Z Chen; Jianxu Chen

Rethinking deep learning in bioimaging through a data centric lens

Jiajun Cao, Jan Wenzel, Shanghang Zhang, Josephine Lampe, Hongxiao Wang, Jiachen Yao, Zhicheng Zhang, Shuo Zhao, Yu Zhou, Chao Chen, Markus Schwaninger, Jufeng Yang, Danny Z Chen, Jianxu Chen

Institute of Experimental and Clinical Pharmacology and Toxicology

4 Citations (Scopus)

Abstract

Deep learning has become essential in bioimaging for tasks. By examining data-centric strategies in general AI and revisiting existing deep learning methods in bioimaging, we describe a prototypical “BioData-Centric AI” framework. For AI users in bioimaging, this framework promotes a more practical approach beyond simply annotating large datasets or relying on a universal model. For method developers, it highlights key research directions to enhance AI toolboxes for the bioimaging community.

Original language	English
Article number	29
Journal	NPJ Imaging
Volume	3
Issue number	1
Pages (from-to)	29
ISSN	2948-197X
Publication status	Published - 26.06.2025

Funding

Funders	Funder number
Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen
European Research Council
Horizon 2020 Framework Programme	810331
Deutsche Forschungsgemeinschaft	WE 6456/1-1
National Science and Technology Major Project	2022ZD0117800
Bundesministerium für Forschung, Technologie und Raumfahrt	161L0272
Natural Science Foundation of Beijing Municipality	4254093

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Cite this

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AU - Cao, Jiajun

AU - Wenzel, Jan

AU - Zhang, Shanghang

AU - Lampe, Josephine

AU - Wang, Hongxiao

AU - Yao, Jiachen

AU - Zhang, Zhicheng

AU - Zhao, Shuo

AU - Zhou, Yu

AU - Chen, Chao

AU - Schwaninger, Markus

AU - Yang, Jufeng

AU - Chen, Danny Z

AU - Chen, Jianxu

PY - 2025/6/26

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N2 - Deep learning has become essential in bioimaging for tasks. By examining data-centric strategies in general AI and revisiting existing deep learning methods in bioimaging, we describe a prototypical “BioData-Centric AI” framework. For AI users in bioimaging, this framework promotes a more practical approach beyond simply annotating large datasets or relying on a universal model. For method developers, it highlights key research directions to enhance AI toolboxes for the bioimaging community.

AB - Deep learning has become essential in bioimaging for tasks. By examining data-centric strategies in general AI and revisiting existing deep learning methods in bioimaging, we describe a prototypical “BioData-Centric AI” framework. For AI users in bioimaging, this framework promotes a more practical approach beyond simply annotating large datasets or relying on a universal model. For method developers, it highlights key research directions to enhance AI toolboxes for the bioimaging community.

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Rethinking deep learning in bioimaging through a data centric lens

Abstract

Funding

UN SDGs

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