生物图像分析研究者终于有了一个能理解自然语言并自动生成可复现工作流的工具——Agentic-J 解决了跨工具集成和编程门槛的痛点，做细胞生物学或显微镜分析的团队值得一试。
Agentic-J 是一个容器化的多智能体AI助手，专为ImageJ/Fiji设计，使生物学家能用自然语言指定分析任务，如细胞核分割、细胞追踪和多条件量化。该智能体生成可执行的脚本并组织成有文档的项目结构，确保每个分析决策可追溯，工作流可复现或共享。其专门子智能体负责插件管理、代码生成、调试、质量保证和统计报告。论文展示了系统设计、真实生物显微镜图像分析工作流及技术实现细节。
Agentic-J: An AI Agent for Biological Microscopy Image Analysis
Biological image analysis increasingly demands integration across heterogeneous tools, programming environments, and domain knowledge that few researchers can command simultaneously. We present Agentic-J, a containerised, multi-agent AI assistant, primarily for ImageJ/Fiji that enables biologists to specify analysis tasks in natural language, from nuclei segmentation and cell tracking to multi-condition quantification. The agent generates executable scripts organised into a documented project structure, so every analysis decision is traceable and the workflow can be reproduced or shared. The specialised sub-agents handle plugin management, code generation, debugging, quality assurance, and statistical reporting. In this paper we introduce the system's design, demonstrate real biological microscopy image analysis workflows, and detailed the technical implementation.