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CA-Net: Enhanced Explainable Segmentation by Suesarn Wilainuch is a document available to read on EtoBox.
What is CA-Net: Enhanced Explainable Segmentation about?
CA-Net is a comprehensive attention convolutional neural network proposed for explainable medical image segmentation. It uses multiple attention mechanisms to help the network focus on important spatial positions, channels, and scales. This improves segmentation accuracy and explainability compared to methods like U-Net. CA-Net achieved Dice scores of 92.08% for skin lesion segmentation and 87.08% and 95.88% for placenta and fetal brain segmentation in MRI, outperforming U-Net. It also has a smaller model s
- Author
- Suesarn Wilainuch
- Language
- EN