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On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learning architectures such as U-Net and its variants, performance degradation across datasets remains a major challenge, particularly under domain shift and limited annotated data. To address this issue, this study systematically evaluates how individual MRI sequences influence model robustness across two well-known datasets. A ResUNet-based framework is employed, where each modality is trained independently to isolate its effect under a controlled

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