7 papers
DCAU-Net: Differential Cross Attention and Channel-Spatial Feature Fusion for Medical Image Segmentation
Yanxin Li, Hui Wan, Libin Lan
Accurate medical image segmentation requires effective modeling of both long-range dependencies and fine-grained boundary details. While transformers mitigate the issue of insuffic…
TAP-SLF: Parameter-Efficient Adaptation of Vision Foundation Models for Multi-Task Ultrasound Image Analysis
Hui Wan, Libin Lan
Executing multiple tasks simultaneously in medical image analysis, including segmentation, classification, detection, and regression, often introduces significant challenges regard…
TCSAFormer: Efficient Vision Transformer with Token Compression and Sparse Attention for Medical Image Segmentation
Zunhui Xia, Hongxing Li, Libin Lan
In recent years, transformer-based methods have achieved remarkable progress in medical image segmentation due to their superior ability to capture long-range dependencies. However…
MedFormer: Hierarchical Medical Vision Transformer with Content-Aware Dual Sparse Selection Attention
Zunhui Xia, Hongxing Li, Libin Lan
Medical image recognition serves as a key way to aid in clinical diagnosis, enabling more accurate and timely identification of diseases and abnormalities. Vision transformer-based…
DMAF-Net: An Effective Modality Rebalancing Framework for Incomplete Multi-Modal Medical Image Segmentation
Libin Lan, Hongxing Li, Zunhui Xia +1
Incomplete multi-modal medical image segmentation faces critical challenges from modality imbalance, including imbalanced modality missing rates and heterogeneous modality contribu…
Cross-Modal Clustering-Guided Negative Sampling for Self-Supervised Joint Learning from Medical Images and Reports
Libin Lan, Hongxing Li, Zunhui Xia +5
Learning medical visual representations directly from paired images and reports through multimodal self-supervised learning has emerged as a novel and efficient approach to digital…
DSSAU-Net:U-Shaped Hybrid Network for Pubic Symphysis and Fetal Head Segmentation
Zunhui Xia, Hongxing Li, Libin Lan
In the childbirth process, traditional methods involve invasive vaginal examinations, but research has shown that these methods are both subjective and inaccurate. Ultrasound-assis…