221 citations · 358 across the 11 of their papers we have counts for
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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…