SwinBTS: A Method for 3D Multimodal Brain Tumor Segmentation Using Swin Transformer.

ABSTRACT: Brain tumor semantic segmentation is a critical medical image processing work, which aids clinicians in diagnosing patients and determining the extent of lesions. Convolutional neural networks (CNNs) have demonstrated exceptional performance in computer vision tasks in recent years. For 3D medical image tasks, deep convolutional neural networks based on an encoder-decoder structure and skip-connection have been frequently used. However, CNNs have the drawback of being unable to learn global and remote semantic information well. On the other hand, the transformer has recently found success in natural language processing and computer vision as a result of its usage of a self-attention mechanism for global information modeling. For demanding prediction tasks, such as 3D medical picture segmen

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC9221215 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature