Automated Detection of Abnormalities in Zebrafish Development

2026-05-11

AI Summary

This study addresses the inefficiency and scarcity of large-scale annotated data in traditional manual detection of zebrafish embryonic developmental abnormalities. To overcome these limitations, the authors construct the first large-scale, high-resolution zebrafish embryo microscopy image sequence dataset with fine-grained temporal annotations and propose the first Transformer-based spatiotemporal feature fusion model for early automatic prediction of developmental anomalies. The method achieves 98% accuracy in egg viability classification and 92% accuracy in teratogenicity assessment from toxicological exposure, substantially advancing the automation and standardization of zebrafish-based toxicity analysis.

Abstract

Zebrafish embryos are a valuable model for drug discovery due to their optical transparency and genetic similarity to humans. However, current evaluations rely on manual inspection, which is costly and labor-intensive. While machine learning offers automation potential, progress is limited by the lack of comprehensive datasets. To address this, we introduce a large-scale dataset of high-resolution microscopic image sequences capturing zebrafish embryonic development under both control conditions and exposure to compounds (3,4-dichloroaniline). This dataset, with expert annotations at fine-grained temporal levels, supports two benchmarking tasks: (1) fertility classification, assessing zebrafish egg viability (130,368 images), and (2) toxicity assessment, detecting malformations induced by toxic exposure over time (55,296 images). Alongside the dataset, we present the first transformer-based baseline model that integrates spatiotemporal features to predict developmental abnormalities at early stages. Experimental results present the model's effectiveness, achieving 98% accuracy in fertility classification and 92% in toxicity assessment. These findings underscore the potential of automated approaches to enhance zebrafish-based toxicity analysis.

Problem

• zebrafish
• developmental abnormalities
• toxicity assessment
• fertility classification
• automated detection

Innovation

• zebrafish development
• large-scale dataset
• transformer-based model
• spatiotemporal features
• automated toxicity assessment