提出新基准解决肺部CT分割中的患者数据泄露问题
CTSCAN: Evaluation Leakage in Chest CT Segmentation and a Reproducible Patient-Disjoint Benchmark
- 构建患者无关的多源胸部CT分割基准，避免图像跨病例重复
- 去除患者重用后分割性能下降69%（Dice）和76.5%（IoU）
- 提供可复现的训练-测试流程，适合医疗影像模型严谨评估
当前胸部CT分割性能报告可能因训练与测试集混用同一研究的切片而严重虚高。本文提出CTSCAN，一个可复现的多源胸部CT分割基准与研究工具包，旨在衡量在患者无关评估下的真实性能。该基准包含来自PleThora、MedSeg SIRM和LongCIU的89个病例，我们发现原始的切片-PNG工作流导致训练、验证和测试集间几乎完全的病例重用。通过在相同FPN+EfficientNet-B0配置下进行多种子协议测试，在12轮训练中，切片混合方案达到0.6665前景Dice和0.5031前景IoU；而患者分离方案仅达0.2066 Dice和0.1181 IoU。去除患者重用使前景Dice下降0.4599（相对下降69.00%），前景IoU下降0.3850（相对下降76.52%）。CTSCAN提供确定性划分清单、明确的弱监督控制、脚本化多种子协议与可复现的图表生成，为患者无关的胸部CT评估提供可复用基础。
原文摘要 · Abstract (English)
Reported chest CT segmentation performance can be strongly inflated when train and test partitions mix slices from the same study. We present CTSCAN, a reproducible multi-source chest CT benchmark and research stack designed to measure what survives under patient-disjoint evaluation. The current four-class artifact aggregates 89 cases from PleThora, MedSeg SIRM, and LongCIU, and we show that the original slice-PNG workflow induces near-complete case reuse across train, validation, and test. Using the playground environment, we run a multi-seed protocol sweep with the same FPN plus EfficientNet-B0 control configuration under slice-mixed and case-disjoint evaluation. Across 3 seeds and 12 epochs per seed, the slice-mixed protocol reaches 0.6665 foreground Dice and 0.5031 foreground IoU, whereas the case-disjoint protocol reaches 0.2066 Dice and 0.1181 IoU. Removing patient reuse therefore reduces foreground Dice by 0.4599 absolute (69.00% relative) and foreground IoU by 0.3850 absolute (76.52% relative). CTSCAN packages the corrected benchmark with deterministic split manifests, explicit weak-supervision controls, a scripted multi-seed protocol sweep, and reproducible figure generation, providing a reusable basis for patient-disjoint chest CT evaluation.
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