LANet for medical image segmentation

The paper presents an original LANet model for improving medical image segmentation results based on MobileViT neural network. The developed and integrated Efficient Fusion Attention and Adaptive Feature Fusion blocks improve the quality of feature extraction and reduce data redundancy. The effectiveness of the presented blocks is validated by multiple experiments, including accuracy evaluation on different datasets, based on metrics such as Dice, Precision, Recall, mIoU, model performance evaluation, and ablation study.