7 papers
Hierarchical Feature Learning for Medical Point Clouds via State Space Model
Guoqing Zhang, Jingyun Yang, Yang Li
Deep learning-based point cloud modeling has been widely investigated as an indispensable component of general shape analysis. Recently, transformer and state space model (SSM) hav…
Flemme: A Flexible and Modular Learning Platform for Medical Images
Guoqing Zhang, Jingyun Yang, Yang Li
As the rapid development of computer vision and the emergence of powerful network backbones and architectures, the application of deep learning in medical imaging has become increa…
High-Fidelity Medical Shape Generation via Skeletal Latent Diffusion
Guoqing Zhang, Jingyun Yang, Siqi Chen +2
Anatomy shape modeling is a fundamental problem in medical data analysis. However, the geometric complexity and topological variability of anatomical structures pose significant ch…
Learning What is Worth Learning: Active and Sequential Domain Adaptation for Multi-modal Gross Tumor Volume Segmentation
Jingyun Yang, Guoqing Zhang, Jingge Wang +1
Accurate gross tumor volume segmentation on multi-modal medical data is critical for radiotherapy planning in nasopharyngeal carcinoma and glioblastoma. Recent advances in deep neu…
Hierarchical Part-based Generative Model for Realistic 3D Blood Vessel
Siqi Chen, Guoqing Zhang, Jiahao Lai +5
Advancements in 3D vision have increased the impact of blood vessel modeling on medical applications. However, accurately representing the complex geometry and topology of blood ve…
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation
Shutong Duan, Jingyun Yang, Yang Tan +3
How to mitigate negative transfer in transfer learning is a long-standing and challenging issue, especially in the application of medical image segmentation. Existing methods for r…