A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities

arXiv:2404.14019v1 Announce Type: new
Abstract: Existing brain tumor segmentation methods usually utilize multiple Magnetic Resonance Imaging (MRI) modalities in brain tumor images for segmentation, which can achieve better segmentation performance. However, in clinical applications, some modalities are missing due to resource constraints, leading to severe degradation in the performance of methods applying complete modality segmentation. In this paper, we propose a Multimodal feature distillation with Convolutional Neural Network (CNN)-Transformer hybrid network (MCTSeg) for accurate brain tumor segmentation with missing modalities. …

arxiv brain cnn cs.cv distillation eess.sp feature multimodal network segmentation stat.ap transformer transformer network type