677 citations · 1.2k across the 9 of their papers we have counts for
9 papers
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning
Tongxue Zhou, Alexandra Noeuveglise, Romain Modzelewski +4
Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are easier to recurrent even after standard treatment. Therefore, developing a method to predi…
Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities
Tongxue Zhou, Stéphane Canu, Pierre Vera +1
Using multimodal Magnetic Resonance Imaging (MRI) is necessary for accurate brain tumor segmentation. The main problem is that not all types of MRIs are always available in clinica…
A Tri-attention Fusion Guided Multi-modal Segmentation Network
Tongxue Zhou, Su Ruan, Pierre Vera +1
In the field of multimodal segmentation, the correlation between different modalities can be considered for improving the segmentation results. Considering the correlation between…
Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities
Tongxue Zhou, Stéphane Canu, Pierre Vera +1
Brain tumor is one of the most high-risk cancers which causes the 5-year survival rate of only about 36%. Accurate diagnosis of brain tumor is critical for the treatment planning.…
Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities
Tongxue Zhou, Stéphane Canu, Pierre Vera +1
Magnetic Resonance Imaging (MRI) is a widely used imaging technique to assess brain tumor. Accurately segmenting brain tumor from MR images is the key to clinical diagnostics and t…
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint
Tongxue Zhou, Stéphane Canu, Pierre Vera +1
In the field of multimodal segmentation, the correlation between different modalities can be considered for improving the segmentation results. In this paper, we propose a multi-mo…
A review: Deep learning for medical image segmentation using multi-modality fusion
Tongxue Zhou, Su Ruan, Stéphane Canu
Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusi…
An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism
Tongxue Zhou, Stéphane Canu, Su Ruan
The coronavirus disease (COVID-19) pandemic has led to a devastating effect on the global public health. Computed Tomography (CT) is an effective tool in the screening of COVID-19.…
Brain tumor segmentation with missing modalities via latent multi-source correlation representation
Tongxue Zhou, Stéphane Canu, Pierre Vera +1
Multimodal MR images can provide complementary information for accurate brain tumor segmentation. However, it's common to have missing imaging modalities in clinical practice. Sinc…