9 citations · 9 across the 7 of their papers we have counts for
5 papers · 1 filter
Refining 3D Medical Segmentation with Verbal Instruction
Kangxian Xie, Jiancheng Yang, Nandor Pinter +3
Accurate 3D anatomical segmentation is essential for clinical diagnosis and surgical planning. However, automated models frequently generate suboptimal shape predictions due to fac…
Volumetric Directional Diffusion: Anchoring Uncertainty Quantification in Anatomical Consensus for Ambiguous Medical Image Segmentation
Chao Wu, Mahesh Bhosale, Kangxian Xie +3
Ambiguous 3D medical image segmentation often involves boundaries where different expert delineations are non-identical yet clinically plausible. Modeling such inter-observer varia…
Learning Topology-Aware Implicit Field for Unified Pulmonary Tree Modeling with Incomplete Topological Supervision
Ziqiao Weng, Jiancheng Yang, Kangxian Xie +2
Pulmonary trees extracted from CT images frequently exhibit topological incompleteness, such as missing or disconnected branches, which substantially degrades downstream anatomical…
S-TTA: Scale-Style Selection for Test-Time Augmentation in Biomedical Image Segmentation
Kangxian Xie, Siyu Huang, Sebastian Andres Cajas Ordonez +2
Deep-learning models have been successful in biomedical image segmentation. To generalize for real-world deployment, test-time augmentation (TTA) methods are often used to transfor…
Efficient Anatomical Labeling of Pulmonary Tree Structures via Deep Point-Graph Representation-based Implicit Fields
Kangxian Xie, Jiancheng Yang, Donglai Wei +2
Pulmonary diseases rank prominently among the principal causes of death worldwide. Curing them will require, among other things, a better understanding of the complex 3D tree-shape…