2 citations · 3 across the 5 of their papers we have counts for
5 papers
Few-Shot 3D Volumetric Segmentation with Multi-Surrogate Fusion
Meng Zheng, Benjamin Planche, Zhongpai Gao +3
Conventional 3D medical image segmentation methods typically require learning heavy 3D networks (e.g., 3D-UNet), as well as large amounts of in-domain data with accurate pixel/voxe…
Automating Catheterization Labs with Real-Time Perception
Fan Yang, Benjamin Planche, Meng Zheng +3
For decades, three-dimensional C-arm Cone-Beam Computed Tomography (CBCT) imaging system has been a critical component for complex vascular and nonvascular interventional procedure…
Self-supervised 3D Patient Modeling with Multi-modal Attentive Fusion
Meng Zheng, Benjamin Planche, Xuan Gong +3
3D patient body modeling is critical to the success of automated patient positioning for smart medical scanning and operating rooms. Existing CNN-based end-to-end patient modeling…
IBAFormer: Intra-batch Attention Transformer for Domain Generalized Semantic Segmentation
Qiyu Sun, Huilin Chen, Meng Zheng +3
Domain generalized semantic segmentation (DGSS) is a critical yet challenging task, where the model is trained only on source data without access to any target data. Despite the pr…
CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation
Ruihao Xia, Chaoqiang Zhao, Meng Zheng +3
Most nighttime semantic segmentation studies are based on domain adaptation approaches and image input. However, limited by the low dynamic range of conventional cameras, images fa…