AATE-UNet automated assessment of inflammatory response in zebrafish larvae exposed to environmental risks

Ecotoxicology and Environmental Safety 2026 Open access

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Authors: Jiaqi Yang, Lulu Xu, Zhenglin Chen, Tingqiao Ye, Yungui Li, Min Dai, Pei Yang, Peiwu Qin
DOI: 10.1016/j.ecoenv.2026.119939
Cited by: 0
References: 26

Abstract

In the evaluation of drugs/cosmetics toxicology/efficacy on livings, rapid assessment of inflammatory responses in zebrafish models is critical but hindered by labor-intensive manual neutrophil counting. To be addressed, this study developed the innovative AATE-UNet, a deep learning model that automates high-throughput image analysis for precise inflammation quantification. In result, this UNet-based architecture processes lateral zebrafish images to segment complex anatomical regions (yolk sac, spinal cord) and quantify neutrophils with 90 % accuracy (

Fields of Study & Subjects

Zebrafish Biomedical Research Applications Cell Image Analysis Techniques Environmental Toxicology and Ecotoxicology

Publication details

Journal / source
Ecotoxicology and Environmental Safety
Volume
312
Pages
119939–119939
Publication date
26 February 2026
Language
EN