AI RESEARCH
CTSCAN: Evaluation Leakage in Chest CT Segmentation and a Reproducible Patient-Disjoint Benchmark
arXiv CS.CV
•
ArXi:2604.15561v1 Announce Type: cross 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.