
FANCL, a novel deep learning model, leverages feature-guided attention and curriculum learning to overcome limitations of traditional CNNs in segmenting brain metastases (BMs) from MRI, particularly small and irregular lesions, achieving superior performance compared to existing methods.


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fancl-using-feature-guided-attention-and-curriculum-learning-to-improve-brain-metastases-segmentation-in-cnns


FANCL: Using Feature-Guided Attention and Curriculum Learning to Improve Brain Metastases Segmentation in CNNs


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TransUNet model combines Transformer self-attention with U-Net for brain metastases segmentation.


3d-transunet-for-brain-metastases-segmentation-in-brats2023-challenge-report


3D-TransUNet for Brain Metastases Segmentation in BraTS2023 Challenge Report



Effective brain metastases segmentation using 3D-TransUNet model.


3d-transunet-for-brain-metastases-segmentation-in-brats2023-challenge


3D-TransUNet for Brain Metastases Segmentation in BraTS2023 Challenge
