Cancers
Convolutional, State-Space and Transformer Liver-Tumor Segmentation Models Trained on Hepatocellular Carcinoma Fail on the Same External Cases: Lesion Size Outweighs Architecture in Cross-Dataset Generalization
Door Kutlu H, Çolak C en Akbulut S.
Inhoud in het Engels
Abstract
Background/objectives
Architectural innovation is widely assumed to improve the cross-institutional generalization of tumor segmentation models, yet this is rarely tested. We compared three architectural families under an identical, leak-safe protocol in hepatocellular carcinoma (HCC) segmentation.