EfficientUNetViT: Efficient Breast Tumor Segmentation Utilizing UNet Architecture and Pretrained Vision Transformer

EfficientUNetViT: Efficient Breast Tumor Segmentation Utilizing UNet Architecture and Pretrained Vision Transformer

This study introduces a sophisticated neural network structure for segmenting breast tumors. It achieves this by combining a pretrained Vision Transformer (ViT) model with a UNet framework. The UNet architecture, commonly employed for biomedical image segmentation, is further enhanced with depthwise...

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Bibliografiske detaljer
Main Authors: Shokofeh Anari, Gabriel Gomes de Oliveira, Ramin Ranjbarzadeh, Angela Maria Alves, Gabriel Caumo Vaz, Malika Bendechache
Format: Article
Sprog:English
Udgivet: MDPI AG 2024-09-01
Serier:Bioengineering
Fag:
breast cancer
UNet
vision transformer
depthwise separable convolutional
Online adgang:https://www.mdpi.com/2306-5354/11/9/945

Internet

https://www.mdpi.com/2306-5354/11/9/945

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