3 citations · 5 across the 11 of their papers we have counts for
14 papers
SAMI3D-DW: Interactive Segmentation of Any 3D Medical Images
Ping Gong, Shiyuan Su, Fandong Zhang +4
Interactive segmentation of 3D medical images supports quantitative analysis of anatomical structures and disease while allowing users to specify and refine their targets. Despite…
Topology-Driven Transferability Estimation for 3D Medical Vision Foundation Models
Jiaqi Tang, Shaoyang Zhang, Fandong Zhang +3
The growing number of medical vision foundation models highlights the need for effective model selection. However, mainstream selection methods rely on exhaustive fine-tuning, whic…
The Texture-Shape Dilemma: Boundary-Safe Synthetic Generation for 3D Medical Transformers
Jiaqi Tang, Weixuan Xu, Shu Zhang +2
Vision Transformers (ViTs) have revolutionized medical image analysis, yet their data-hungry nature clashes with the scarcity and privacy constraints of clinical archives. Formula-…
Fake It Right: Injecting Anatomical Logic into Synthetic Supervised Pre-training for Medical Segmentation
Jiaqi Tang, Mengyan Zheng, Shu Zhang +2
Vision Transformers (ViTs) excel in 3D medical segmentation but require massive annotated datasets. While Self-Supervised Learning (SSL) mitigates this using unlabeled data, it sti…
LDRNet: Large Deformation Registration Model for Chest CT Registration
Cheng Wang, Qiyu Gao, Fandong Zhang +2
Most of the deep learning based medical image registration algorithms focus on brain image registration tasks.Compared with brain registration, the chest CT registration has larger…
Autoregressive Sequence Modeling for 3D Medical Image Representation
Siwen Wang, Churan Wang, Fei Gao +4
Three-dimensional (3D) medical images, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are essential for clinical applications. However, the need for diverse…