In the process of medical image segmentation,alignment,image histology and computer-aided diagnosis,high-resolution medical images can significantly improve the experimental accuracy.However,the thickness of the acquired image slices is large,which brings difficulties for the subsequent image analysis.The aim of this paper is to use super-resolution reconstruction to change the thick layer data of MRI head into thin layer data.In order to be able to improve the accuracy of super-resolution,we divide the image into small blocks,the target output layer is O_Block,while the input layer is I_Block.the O_Block is in the size of 16×16 pixels.In order to more accurately handle the phenomenon of organizing texture in various different directions,I_Block is larger than O_Block.In the experiment,I_Block was taken as 32×32,48×48,and 64×64,respectively.We used Swin Transformer to realize the super-resolution of MRI images and obtain the super-resolution results of head MRI.The experimental results show that the thick layer image can be input better to predict the thin layer image by this experiment.
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