Search Results for author:
Found 9 papers, 0 papers with code
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning
In this paper, we present a deep learning-based brain tumor recurrence location prediction network.
Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities
Based on the fact that there is a strong correlation between MR modalities of the same patient, in this work, we propose a novel brain tumor segmentation network in the case of missing one or more modalities.
A Tri-attention Fusion Guided Multi-modal Segmentation Network
Considering the correlation between different MR modalities, in this paper, we propose a multi-modality segmentation network guided by a novel tri-attention fusion.
Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities
The proposed network consists of a conditional generator, a correlation constraint network and a segmentation network.
Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities
In addition, multi-modal MR images can provide complementary information for accurate brain tumor segmentation.
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint
Our network includes N model-independent encoding paths with N image sources, a correlation constraint block, a feature fusion block, and a decoding path.
A review: Deep learning for medical image segmentation using multi-modality fusion
Due to their self-learning and generalization ability over large amounts of data, deep learning recently has also gained great interest in multi-modal medical image segmentation.
An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism
The coronavirus disease (COVID-19) pandemic has led to a devastating effect on the global public health.
Brain tumor segmentation with missing modalities via latent multi-source correlation representation
Multimodal MR images can provide complementary information for accurate brain tumor segmentation.
