9 papers · 1 filter
OFD-Net: Teacher-Free Reliable Semi-supervised Medical Image Segmentation with Orthogonal Feature Disentanglement Net of Foreground-Background
Shao-feng Jiang, Zhe-yang Jing, Qin Lu +4
Semi-supervised learning (SSL) is an effective solution for medical image segmentation with limited annotations. Existing SSL methods mainly rely on pseudo-labels generated by teac…
Rethinking the Adaptation of Vision Foundation Models for Efficient Cell Segmentation
Qing Xu, Xiangjian He, Wenting Duan +2
Cell segmentation is critical for computational pathology and biomedical discovery. While recent Vision Foundation Models (VFMs) have demonstrated remarkable universal feature repr…
FreqDINO: Frequency-Guided Adaptation for Generalized Boundary-Aware Ultrasound Image Segmentation
Yixuan Zhang, Qing Xu, Yue Li +6
Ultrasound image segmentation is pivotal for clinical diagnosis, yet challenged by speckle noise and imaging artifacts. Recently, DINOv3 has shown remarkable promise in medical ima…
Co-Seg++: Mutual Prompt-Guided Collaborative Learning for Versatile Medical Segmentation
Qing Xu, Yuxiang Luo, Wenting Duan +1
Medical image analysis is critical yet challenged by the need of jointly segmenting organs or tissues, and numerous instances for anatomical structures and tumor microenvironment a…
SP-Det: Self-Prompted Dual-Text Fusion for Generalized Multi-Label Lesion Detection
Qing Xu, Yanqian Wang, Xiangjian Hea +5
Automated lesion detection in chest X-rays has demonstrated significant potential for improving clinical diagnosis by precisely localizing pathological abnormalities. While recent…
TM-UNet: Token-Memory Enhanced Sequential Modeling for Efficient Medical Image Segmentation
Yaxuan Jiao, Qing Xu, Yuxiang Luo +3
Medical image segmentation is essential for clinical diagnosis and treatment planning. Although transformer-based methods have achieved remarkable results, their high computational…