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MaxViT-UNet for Medical Image Segmentation by Jovana is a document available to read on EtoBox.

What is MaxViT-UNet for Medical Image Segmentation about?

The document presents the Multi-Axis Vision Transformer UNet (MaxViT-UNet), a hybrid architecture designed for medical image segmentation that combines convolutional neural networks and self-attention mechanisms. Experimental results demonstrate that MaxViT-UNet outperforms traditional UNet and Swin-UNet models in segmentation accuracy on multiple datasets. The proposed architecture enhances feature extraction and segmentation efficiency through a novel hybrid decoder and multi-axis self-attention mechanism

Author

Jovana

Language

EN