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Brain Tumor Segmentation with Sequence Dropout by fengli949 is a document available to read on EtoBox.

This study presents a deep convolutional neural network (DCNN) framework for brain tumor segmentation from multi-modal MRI, addressing the challenge of missing MRI sequences through a novel sequence dropout technique. The framework enhances model robustness without compromising performance, as demonstrated by improved segmentation metrics when key sequences are unavailable. Experiments on the RSNA-ASNR-MICCAI BraTS 2021 Challenge dataset confirm the efficacy of the proposed method in handling missing inform

Author

fengli949

Language

EN