In the field of Medical Image Segmentation, deep learning models, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT) models, have been widely researched and applied in recent ...

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The rapid advancement of medical imaging technologies requires the development of advanced, automated, and interpretable diagnostic tools for clinical decision-making. Although convolutional neural ...

To segment medical images with distribution shifts, domain generalization (DG) has emerged as a promising setting to train models on source domains that can generalize to unseen target domains.

With the development of deep learning technology, its application in the field of medical image recognition is more and more extensive. This paper aims to explore the application of convolutional ...

For CT images ( e.g. BTCV multi-organ segmentation), we did not see any difference in terms of performance between these two approaches. hidden_size : this is the size of the hidden layers in the ViT ...