29 citations · 111 across the 23 of their papers we have counts for
7 papers · 1 filter
Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective
Minye Shao, Zeyu Wang, Haoran Duan +5
Precise segmentation of brain tumors, particularly contrast-enhancing regions visible in post-contrast MRI (areas highlighted by contrast agent injection), is crucial for accurate…
K-Space-Aware Cross-Modality Score for Synthesized Neuroimage Quality Assessment
Guoyang Xie, Jinbao Wang, Yawen Huang +4
The problem of how to assess cross-modality medical image synthesis has been largely unexplored. The most used measures like PSNR and SSIM focus on analyzing the structural feature…
Cross-Modal Vertical Federated Learning for MRI Reconstruction
Yunlu Yan, Hong Wang, Yawen Huang +5
Federated learning enables multiple hospitals to cooperatively learn a shared model without privacy disclosure. Existing methods often take a common assumption that the data from d…
mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation
Yao Zhang, Nanjun He, Jiawei Yang +6
Accurate brain tumor segmentation from Magnetic Resonance Imaging (MRI) is desirable to joint learning of multimodal images. However, in clinical practice, it is not always possibl…
Cross-Modality Neuroimage Synthesis: A Survey
Guoyang Xie, Yawen Huang, Jinbao Wang +4
Multi-modality imaging improves disease diagnosis and reveals distinct deviations in tissues with anatomical properties. The existence of completely aligned and paired multi-modali…
FedMed-ATL: Misaligned Unpaired Brain Image Synthesis via Affine Transform Loss
Jinbao Wang, Guoyang Xie, Yawen Huang +3
The existence of completely aligned and paired multi-modal neuroimaging data has proved its effectiveness in the diagnosis of brain diseases. However, collecting the full set of we…
OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images
Yu Chen, Jiawei Chen, Dong Wei +2
Deep learning models, such as the fully convolutional network (FCN), have been widely used in 3D biomedical segmentation and achieved state-of-the-art performance. Multiple modalit…