Author

Henrique Zan Grande

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Preprint Sep 2026

Generalizable Brain Tumor Segmentation with Self-Training and Tumor-Aware Deformations

This work presents an approach to the Generalizability Across Tumors (BraTS-GoAT) task of the BraTS 2026 Challenge, which focuses on robust segmentation of brain tumor sub-regions across a heterogeneous patient population. The proposed method employs the nnU-Net framework with a large residual encoder architecture, int...

Henrique Zan Grande, Jeovane Honorio Alves, R. Laroca et al. · 0 citations

Preprint Aug 2026

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

This study systematically evaluates how individual MRI sequences influence model robustness across two well-known datasets, and shows that the T2f/FLAIR sequence achieves the best cross-dataset performance, with Dice scores exceeding 75%.

Henrique Zan Grande, João G. Pitol, Lucas B. Schuck et al. · 0 citations