Research on Classification of Alzheimer's Disease Based on Vision Transformer
To effectively improve the classification accuracy of magnetic resonance imaging(MRI)for Alzheimer's disease(AD),we propose an LC(Layer-Cut)-ViT method in this paper.This method introduces the self-attention mechanism of the Vision Transformer(ViT)and performs layer-wise segmentation on the MRI images,to enable the model to better understand the global information of the images while emphasizing the inter-slice feature relationships.Additionally,the extraction of brain tissue from the MRI images is further enhanced by employing registration and skull-stripping algorithms,which results in im-proved performance of the model.Experimental results demonstrate that the proposed method exhibits good classification abili-ty for MRI images of Alzheimer's disease.
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维普
