AI 中文总结
针对CT数据准备的可迁移性问题，提出CT-PrepAgent模型，通过有界策略与受控执行实现自适应处理，在公开分割任务与私有DICOM队列中均取得了良好性能。
AI 中文摘要
异构计算机断层扫描（CT）采集及多样化下游任务需求，限制了固定数据准备工作流跨数据源与任务的可迁移性。现有方法通常依赖人工设计或特定数据集的规则，难以在采集条件与分析目标发生变化时无需人工干预即可适配。基于大语言模型（LLM）的智能体已展现出自动化医疗工作流的潜力，但其在自适应CT数据准备方面的潜力仍未得到充分探索。为填补这一空白，我们提出CT-PrepAgent，其通过有界策略与受控确定性执行实现自适应CT数据准备。确定性检查构建结构化的数据-任务配置文件，策略从中确定合格的DICOM序列或预定义的预处理配置文件；受控执行流程在启用时有界恢复地守护、解析、执行并验证决策，否则执行安全隔离。在三项公开CT分割任务中，CT-PrepAgent做出了数据-任务自适应的预处理决策，并取得了最高的宏平均Dice分数。在两个私有原始DICOM队列中，CT-PrepAgent将验证后的输出合格率从61.7%提升至70.0%，且在常见验证输出上取得了相似的配准指标。受控故障与重放测试验证了在测试的故障与漂移设置下的有界恢复、安全隔离及无策略重放能力。
英文摘要
Heterogeneous computed tomography (CT) acquisitions and diverse downstream task requirements limit the transferability of fixed data preparation workflows across data sources and tasks. Existing approaches typically rely on manually designed or dataset-specific rules, making it difficult to accommodate changes in acquisition conditions and analytical objectives without manual intervention. Large language model (LLM)-based agents have shown promise for automating medical workflows, yet their potential for adaptive CT data preparation remains largely unexplored. To bridge this gap, we propose CT-PrepAgent, which enables adaptive CT data preparation through a bounded policy and controlled deterministic execution. Deterministic inspection constructs structured data--task profiles, from which a policy decides an eligible DICOM series or predefined preprocessing profile, while the controlled execution flow guards, resolves, executes, and verifies the decision with bounded recovery when enabled and safe quarantine otherwise. Across three public CT segmentation tasks, CT-PrepAgent derived data-task adaptive preprocessing decisions and achieved the highest macro-average Dice. On two private raw-DICOM cohorts, CT-PrepAgent increased verified output yield from 61.7\% to 70.0\% and yielded similar registration metrics on common verified outputs. Controlled fault and replay tests validate bounded recovery, safe quarantine, and policy-free replay under tested fault and drift settings.
