InfiltrNet fuses CNN and Swin Transformer encoders via cross-attention to predict infiltration risk zones from BraTS MRI data using distance-transform labels and outperforms five baselines.
Imaging sur- rogates of infiltration obtained via multiparametric imaging pattern analysis predict subsequent location of recurrence of glioblastoma
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InfiltrNet: Dual-Branch CNN-Transformer Architecture for Brain Tumor Infiltration Risk Prediction
InfiltrNet fuses CNN and Swin Transformer encoders via cross-attention to predict infiltration risk zones from BraTS MRI data using distance-transform labels and outperforms five baselines.