Bayesian Neural Networks for 2D MRI Segmentation

• URL: http://arxiv.org/abs/2311.14875v3
• Date: Sun, 15 Sep 2024 20:36:12 GMT
• Title: Bayesian Neural Networks for 2D MRI Segmentation
• Authors: Lohith Konathala,
• Abstract summary: We introduce BA U-Net, an uncertainty-aware model for MRI segmentation. BA U-Net delivers accurate, interpretable results, crucial for reliable pathology screening.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Uncertainty quantification is vital for safety-critical Deep Learning applications like medical image segmentation. We introduce BA U-Net, an uncertainty-aware model for MRI segmentation that integrates Bayesian Neural Networks with Attention Mechanisms. BA U-Net delivers accurate, interpretable results, crucial for reliable pathology screening. Evaluated on BraTS 2020, this model addresses the critical need for confidence estimation in deep learning-based medical imaging.

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